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zPmNR~S1Oogqvyu3F=6d0=v$JsT;Xc5RDR6ZS<-;;+0a05Pg%WQm3;li~LtKUetgDl0_NEMq#g-Rn9areq0JXD`kdrX{M zrPHHIJ<4gF{Rq&5piyIViL zblGMryKYiv61@l*QD&HoxEP|sk1(2g$=(t0G{N&-ikxz4tRTNkP`;JS*%8MJKqqe>z&}=ucpq(6x^AAvU(gE3Ov5Zcje``%4sZ~BGTUt z>#fbmnvHxgfx0JLBeJum*gxZq3X!Zk_?~1Er`n=I zXo`QUe!2qNB-j|jOd}7bK}uLpkFoRby3~cfBv{X*b119?>p~W)<)cFecu?ej$K-YG z6?2@rSi?R6k^L=agPhHP7OnWdh{p zcyxx-Qp~T|C|cq7M=UoV;PjbK?8EO-8*O92MVdZk3=halTcR%2CGc|I!cD#1i=^?Q zYyxNqs>|x|wY)_9qGQIArLQGe)rXXK5M$AaF20%VV^) zrosU|^$Y6)0puk965h*L6N@4rIGKf#kg{g=`uZ@3t(=OVP`X_}me! zq+>ZlNQq3`AMtfc{^o1vOdxsCX@5lSdStwrJ!&I?t|Xj(Sqc!aH$~l1P#$mxoGI|m zk|F)Nmqn~C9~Ru)w)<2nKM2q+AcK6$_@YmbY}TkTiy_kGwfvaJDQI9zu8UU(@3Zs^A>hWn4e~nBk%nx!ve_pPvaG``+%NPH$ z;6&l=tB^$E{TQ@hh|xwq>rOq-9kw|9d8j=4b!H8eiZ|mu@Lu=-f6ovl0c@pgF#OPwC2{`#yWbx% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) - -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) %>% - mutate(hits = as.numeric(EAR > 0.1), - endPoint=as.character(endPoint)) %>% - filter(!is.na(EAR)) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemSum2_passive <- chemSumm(chemicalSummary_passive) - -summ1_passive <- siteSumm(chemicalSummary_passive, newSiteKey) - - -## ---- eval=TRUE, echo=FALSE---------------------------------------------- - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) -chemSum2_BM <- chemSumm(chemicalSummary_BM) - - -summary_BM <- siteSumm(chemicalSummary_BM,newSiteKey) - - - - -## ----echo=FALSE, eval=TRUE----------------------------------------------- -library(knitr) -library(pander) -ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)",rep("", 8)) - -df <- data.frame(ws=ws, stringsAsFactors=FALSE) - -names(df) <- c("Water Samples: Organic Waste Compounds") - -pander(df) - - -## ----warning=FALSE, echo=FALSE------------------------------------------- -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "waterSamples.RData") -load(file=filePath) - -waterSamples$site["USGS-04157005" == waterSamples$site] <- "USGS-04157000" - - -pCodeSummary <- select(pCodeInfo, srsname, casrn, parameter_units, mlWt) - -detectionLimits <- waterSamples[,grep("detectionLimit", names(waterSamples))] -detectionLimits <- na.omit(detectionLimits) - -detLevels <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue,-class, -minDetLevel,-chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - - -## ---- echo=FALSE, results='asis'----------------------------------------- - -datatable(chemSum2[,-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) - -## ----message=FALSE, results='asis', echo=FALSE--------------------------- - - -chemSum3 <- chemicalSummary %>% - group_by(chnm, class, site, endPoint) %>% - summarize(hits=as.numeric(any(hits > 0)), - maxEAR=max(EAR)) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits), - maxEAR=max(maxEAR)) %>% - rename(assay_component_endpoint_name=endPoint) %>% - data.table() %>% - left_join(data.table(endPointInfo), by="assay_component_endpoint_name") %>% - select(chnm, maxEAR, freq, nSites, - endPoint=assay_component_endpoint_name, class, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(chemSum3[,-4]), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -endpointSummary <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -endpointSummary <- endpointSummary %>% - select(endPoint, maxEAR, freq, nSites, - endPoint, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(endpointSummary), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("End Point","Maximum EAR","Fraction of Sites with Hits","nSites","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - - -## ---- echo=FALSE, results='asis'----------------------------------------- -summary_display <- left_join(summary, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display, rownames = FALSE, - colnames=c("Station Name","Fraction of Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -siteLimits <- filter(summary_display, freq>0) %>% - arrange(desc(nChem), desc(nEndPoints)) %>% - select(site,nEndPoints,nChem, nSamples) - - -summary_display2 <- chemicalSummary %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sToxWS <- ggplot(summary_display2, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$site) + - scale_y_log10(limits=c(0.03,5000)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.07, - label=siteLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.045, - label=siteLimits$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.03, - label=siteLimits$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - - -g_sToxWS <- ggplotGrob(sToxWS) -g_sToxWS$layout$clip[g_sToxWS$layout$name=="panel"] <- "off" -grid.draw(g_sToxWS) - - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -chemLimits <- filter(chemSum2, freq>0) %>% - arrange(desc(freq),desc(nEndPoints)) %>% - select(chnm, nEndPoints, freq) %>% - mutate(freq=sprintf("%.0f",100*freq)) - -chemicalSummary_display <- chemicalSummary %>% - filter(EAR>=0.1) - -chemToxWS <- ggplot(chemicalSummary_display, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits$chnm) + - scale_y_log10(limits=c(0.045,5000)) + - labs(x = "Chemical Name")+ - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.07, - label=chemLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.045, - label=chemLimits$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.045), ymax = log10(0.045)) - -g_chemToxWS <- ggplotGrob(chemToxWS) -g_chemToxWS$layout$clip[g_chemToxWS$layout$name=="panel"] <- "off" -grid.draw(g_chemToxWS) - - -## ----echo=FALSE, eval=TRUE----------------------------------------------- -library(knitr) -library(pander) -# ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)") - -df <- data.frame(ps=ps, stringsAsFactors=FALSE) - -names(df) <- c("Passive Samples") - -pander(df) - - -## ----warning=FALSE, echo=FALSE------------------------------------------- - -detLevels_passive <- select(passiveData, Chemical, MQL, CAS, class) %>% - right_join(endPoint_passive, by=c("CAS"="casn")) %>% - select(-mlWt, -conversion, -Chemical, -CAS) %>% - gather(endPoint,endPointValue,-MQL,-chnm, -Units,-class) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=MQL/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel=MQL) %>% - arrange(desc(EAR)) - - -datatable(detLevels_passive, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - - -## ---- echo=FALSE, results='asis'----------------------------------------- -chemSum2_passive_dt <- chemSum2_passive[,-6:-7] %>% - filter(freq > 0) - -datatable(chemSum2_passive_dt, rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits")) %>% - formatRound(c("maxEAR", "freq"), digits = 4) - - -## ----message=FALSE, results='asis', echo=FALSE--------------------------- - - -chemSum3_passive <- chemicalSummary_passive %>% -# group_by(chnm, class, site, endPoint) %>% -# summarize(hits= as.numeric(any(EAR > 0.1))) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits)) - -chemSum4_passive <- chemicalSummary_passive %>% - group_by(chnm, class, endPoint) %>% - summarize(maxEAR=max(EAR), - nSamples=1) %>% - left_join(chemSum3_passive, by=c("chnm","class","endPoint")) %>% - select(chnm, class, freq, maxEAR, nSamples, endPoint) %>% - left_join(endPointInfo, by=c("endPoint"="assay_component_endpoint_name")) %>% - select(chnm, maxEAR, freq, endPoint, class, contains("intended_target_")) %>% - rename(type=intended_target_type, - type_sub=intended_target_type_sub, - family=intended_target_family, - family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) %>% - filter(freq > 0) - - - datatable(distinct(chemSum4_passive), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -## ---- echo=FALSE, results='asis'----------------------------------------- -summary_display_passive <- left_join(summ1_passive, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -summary_display_passive <- summary_display_passive[,c(-2,-3)] -datatable(summary_display_passive, rownames = FALSE, - colnames=c("Station Name", "Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR", "Ag [%]", "Urban [%]")) %>% -# options = list(pageLength = 50)) %>% - formatRound(c("maxEAR"), digits = 2) - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -summary_display1_passive <- transform(summary_display_passive, - site = reorder(site, order(nChem,decreasing=TRUE))) - -siteLimits_passive <- filter(summary_display_passive, nChem>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem) - -summary_display2_passive <- chemicalSummary_passive %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sp <- ggplot(summary_display2_passive, aes(x=site, y=EAR)) + - geom_point() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - ylim(-1,10) + - scale_x_discrete(limits=siteLimits_passive$site)+ - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-0.5, label=siteLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-1, label=siteLimits_passive$nChem),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -1, ymax = -1) - -g_sp <- ggplotGrob(sp) -g_sp$layout$clip[g_sp$layout$name=="panel"] <- "off" -grid.draw(g_sp) - - - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -chemLimits_passive <- filter(chemSum2_passive, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq=sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, nSites) - -chemicalSummary_display_passive <- chemicalSummary_passive %>% - filter(EAR>=0.1) - -cp <- ggplot(chemicalSummary_display_passive, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - ylim(-1,10) + - scale_x_discrete(limits=chemLimits_passive$chnm) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-0.5, - label=chemLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-1, - label=chemLimits_passive$nSites),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Sites:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -1, ymax = -1) - - -g_cp <- ggplotGrob(cp) -g_cp$layout$clip[g_cp$layout$name=="panel"] <- "off" -grid.draw(g_cp) - - -## ----warning=FALSE, echo=FALSE------------------------------------------- - -detLevels_BM <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint_bm, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn) %>% - gather(endPoint,endPointValue,-class, -minDetLevel,-chnm,-Units) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels_BM, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - - -## ---- echo=FALSE, results='asis'----------------------------------------- - -datatable(chemSum2_BM[-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) - -## ---- echo=FALSE, results='asis'----------------------------------------- -summary_display_BM <- left_join(summary_BM, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display_BM, rownames = FALSE, - colnames=c("Station Name","Fraction Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -siteLimits_BM <- filter(summary_display_BM, freq>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem,nSamples) - -summary_display2_BM <- chemicalSummary_BM %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - - -sBenchWS <- ggplot(summary_display2_BM, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits_BM$site) + - scale_y_log10(limits=c(0.03,250)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.07, - label=siteLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.045, - label=siteLimits_BM$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.03, - label=siteLimits_BM$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - -g_sBenchWS <- ggplotGrob(sBenchWS) -g_sBenchWS$layout$clip[g_sBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_sBenchWS) - - - -## ----fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE---- - -chemLimits_BM <- filter(chemSum2_BM, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq = sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, freq) - -chemicalSummary_display_BM <- chemicalSummary_BM %>% - filter(EAR>=0.1) - -cBenchWS <- ggplot(chemicalSummary_display_BM, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits_BM$chnm) + - scale_y_log10(limits=c(0.045,250)) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.07, - label=chemLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.045, - label=chemLimits_BM$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.045), ymax = log10(0.045)) - -g_cBenchWS <- ggplotGrob(cBenchWS) -g_cBenchWS$layout$clip[g_cBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_cBenchWS) - -## ----echo=FALSE---------------------------------------------------------- -# ToxCast Water Samples: -toxWS <- chemSum2 %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm,class,freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive <- chemSum2_passive %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive$Class[toxPassive$Class == "PAHs"] <- "PAH" - -tradWS <- chemSum2_BM %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -tradWS <- tradWS[1:20,1:2] -toxPassive <- toxPassive[1:20,1:2] -toxWS <- toxWS[1:20,1:2] - -combo <- cbind(toxWS, toxPassive, tradWS) -names(combo) <- c("ToxCast-Water Samples: Chemical", "ToxCast-Water Samples: Class","ToxCast-Passive: Chemical", "ToxCast-Passive: Class","WQG-Water Samples: Chemical", "WQG-Water Samples: Class") -# emphasize.strong.cells(which(combo == "PAH", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, style = 'simple', split.table = Inf) - - - -## ---- echo=FALSE, results='asis'----------------------------------------- -formattable(combo, list( - 'ToxCast-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'ToxCast-Passive: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'WQG-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))) -)) - -# emphasize.strong.cells(which(combo == "Herbicide" | combo == "Insecticide", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, split.table = Inf) - -## ---- echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5---- -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapData <- left_join(stationINFO, summary, by=c("shortName"="site")) -mapData <- mapData[!is.na(mapData$dec.lat.va),] -mapData <- mapData[!is.na(mapData$nChem),] - - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,5,10,100,1000,2500)#seq(0,2500, 500) # This is maxEAR - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(5000,15000, 500) -mapData$sizes <- rad[as.numeric(cut(mapData$nChem, c(-1:19)))] - -pal = colorBin(col_types, mapData$maxEAR, bins = leg_vals) - -m = leaflet(mapData) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0('',mapData$Station.Name,"
", - "', - "', - "', - "', - "
Frequency",sprintf("%1.1f",mapData$freq),'
nSample",mapData$nSamples,'
maxEAR",sprintf("%1.1f",mapData$maxEAR),'
nChem",mapData$nChem,'
nEndPoints",mapData$nEndPoints,'
') - , - fillColor = ~pal(maxEAR), - weight = 1, - color = "black", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, - opacity = 0.8, - title = 'Maximum EAR') - -m - - -## ---- echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5---- - -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapDataPassive <- left_join(stationINFO, summ1_passive, by=c("shortName"="site")) -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$dec.lat.va),] -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,2,3,5,7,9)#seq(0,2500, 500) # This is maxEAR scale - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(2500,15000, 2500) -mapDataPassive$sizes <- rad[as.numeric(cut(mapDataPassive$nChem, c(-1,0,1,2,3)))] -mapDataPassive$sizes[is.na(mapDataPassive$sizes)] <- 1000 - -pal = colorBin(col_types, mapDataPassive$maxEAR, bins = leg_vals) - - -map2 = leaflet(mapDataPassive) %>% -# addProviderTiles("Hydda.Full") %>% # There are more maybe worth looking at - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0("",mapDataPassive$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f",mapDataPassive$maxEAR),'
nChem",mapDataPassive$nChem,'
nEndPoints",mapDataPassive$nEndPoints,'
'), - fillColor = ~pal(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map2 - - -## ----echo=FALSE, results='asis', fig.width=7, fig.height=5--------------- -mapDataWQ <- left_join(stationINFO, summary_BM, by=c("shortName"="site")) -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$dec.lat.va),] -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals_BM <- c(0,1,25,50,75,100,125)#seq(0,2500, 500) # This is maxEAR scale - -colsWQ <- colorNumeric(col_types, domain = leg_vals_BM) -radWQ <- seq(2500,15000, 2500) -mapDataWQ$sizes <- rad[as.numeric(cut(mapDataWQ$nChem, c(-1,0,1,5,10)))] -mapDataWQ$sizes[is.na(mapDataWQ$sizes)] <- 1000 - -palWQ = colorBin(col_types, mapDataWQ$maxEAR, bins = leg_vals_BM) - - -map4 = leaflet(mapDataWQ) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup=paste0("",mapDataWQ$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f", mapDataWQ$maxEAR),'
nChem",mapDataWQ$nChem,'
nEndPoints", mapDataWQ$nEndPoints,'
'), - fillColor = ~palWQ(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map4 - - diff --git a/inst/doc/SummaryToxCast.Rmd b/inst/doc/SummaryToxCast.Rmd deleted file mode 100644 index 8753786a..00000000 --- a/inst/doc/SummaryToxCast.Rmd +++ /dev/null @@ -1,975 +0,0 @@ ---- -title: "Assessment of Potential Biological Effects in Great Lakes Tributaries Using ToxCast with Comparisons to Assessment Using Water Quality Guidelines." -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{ToxEval Summary} - \usepackage[utf8]{inputenc} ---- - -```{r message=FALSE, echo=FALSE} -library(grid) -library(pander) -library(dplyr) -library(tidyr) -library(DT) -library(toxEval) -library(knitr) -library(leaflet) -library(formattable) -library(ggplot2) -library(gridExtra) -library(data.table) - -pCodeInfo <- pCodeInfo -wData <- wData -endPointInfo <- endPointInfo -# AC50 data provided in the toxEval package: -AC50gain <- AC50gain -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -endPoint <- endPointToxCreate(pCodeInfo) - -# packagePath <- system.file("extdata", package="toxEval") -# filePath <- file.path(packagePath, "waterSamples.RData") -# load(file=filePath) -######################## - #Correct DEET: - # casDEET <- AC50gain$casn[AC50gain$chnm == "DEET"] - # pCodeDEET <- pCodeInfo$parameter_cd[pCodeInfo$casrn == casDEET] - # dlDEET <- min(waterSamples$valueToUse_61947, na.rm = TRUE) - # waterSamples$qualifier_61947 <- ifelse(waterSamples$valueToUse_61947 <= dlDEET*4, "<", "") -######################## -# Just removing DEET: -# waterSamples <- waterSamples[,-grep("61947",x = names(waterSamples))] -# pCodeInfo <- pCodeInfo[pCodeInfo$parameter_cd != "61947",] -# waterSamples$site["USGS-04157005" == waterSamples$site] <- "USGS-04157000" -# -# waterSamplePCodes <- names(waterSamples)[grep("valueToUse", -# names(waterSamples))] -# waterSamplePCodes <- sapply(strsplit(waterSamplePCodes, "_"), function(x) x[2]) -# -# qualColumns <- grep("qualifier", names(waterSamples)) -# valColumns <- grep("valueToUse", names(waterSamples)) -# -# waterData <- waterSamples[,valColumns] -# waterData[waterSamples[,qualColumns] == "<"] <- 0 -# -# wData <- cbind(waterSamples[,1:2],waterData) -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -chemSum2 <- chemSumm(chemicalSummary) - -summary <- siteSumm(chemicalSummary,newSiteKey) - -``` - - -```{r, echo=FALSE} - -packagePath <- system.file("extdata", package="toxEval") -# filePath <- file.path(packagePath, "passiveData.RData") -# load(file=filePath) - -passiveData <- passiveData - -#passive class info: -passiveCAS <- readRDS(file.path(packagePath, "passiveCAS.rds")) - -# pCodeInfo <- pCodeInfo[pCodeInfo$casrn != "", ] - -# # Some chemicals have 2 rows (different units)... -# # To simplify for now, we'll ignore the duplicate chemicals: -# -# -# passiveData <- left_join(passiveData, passiveCAS, by=c("CAS", "Chemical")) -# passiveData <- passiveData[!duplicated(passiveData$CAS),] -# passiveData$class[passiveData$Chemical == "Hexachlorobenzene (HCB)"] <-"OC Pesticides" -# passiveData$class[passiveData$Chemical == "Pentachloroanisole (PCA)"] <-"OC Pesticides" -# passiveData$class[is.na(passiveData$class)] <-"Pharmaceuticals" -# -# passiveData <- passiveData[,-which(names(passiveData) == "site04249000.1")] - - -unitConversion <- setNames(c(10^6, 10^3), c("pg/L", "ng/L") ) - -AC50_passive <- right_join(AC50gain[,c("casn"), drop=FALSE], - passiveData[,c("CAS", "Units", "mlWt","Chemical")], - by= c("casn" = "CAS")) %>% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) - -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) %>% - mutate(hits = as.numeric(EAR > 0.1), - endPoint=as.character(endPoint)) %>% - filter(!is.na(EAR)) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemSum2_passive <- chemSumm(chemicalSummary_passive) - -summ1_passive <- siteSumm(chemicalSummary_passive, newSiteKey) - -``` - - -```{r, eval=TRUE, echo=FALSE} - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) -chemSum2_BM <- chemSumm(chemicalSummary_BM) - - -summary_BM <- siteSumm(chemicalSummary_BM,newSiteKey) - - - -``` - -# Introduction {#intro} - -## Screening Endpoints Used in Analysis - -* ToxCast: (EPA NCCT) - * "High throughput screening assays" - * In-vitro Exposures to living cells or isolated proteins - * Screens for potential adverse biological effects - * Much is focused on gaining information on biological pathways - * 1860 compounds - * 821 endpoints - * AC50 used for this analysis (concentration at which activity is 50% of its maximum) - * Exposure:Activity Ratio (EAR) = concentration / AC50 -* Established Water quality guidelines - * Water sample analysis (not complete for passive samplers yet) - * USEPA - * Canadian Council of Ministers of the Environment - * USGS - * Literature - -## Matches of Screening Endpoints -* Which chemicals are included in ToxCast and Water Quality Guideline assessments? - + Water samples - * `r length(unique(chemSum2$chnm))` compounds of `r nrow(pCodeInfo)` total - * `r paste(unique(chemSum2$class), collapse=", ")` - + Passive samplers - * `r length(unique(chemSum2_passive$chnm))` compounds of `r length(unique(passiveData$Chemical))` total - * `r paste(unique(chemSum2_passive$class), collapse=", ")` -* Water Quality Guidelines - + Water samples - * `r length(unique(chemSum2_BM$chnm))` compounds of `r nrow(pCodeInfo)` total - * `r paste(unique(chemSum2_BM$class), collapse=", ")` - - -# ToxCast, Water Sample Data {#toxWS} - -Water samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis. - -```{r echo=FALSE, eval=TRUE} -library(knitr) -library(pander) -ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)",rep("", 8)) - -df <- data.frame(ws=ws, stringsAsFactors=FALSE) - -names(df) <- c("Water Samples: Organic Waste Compounds") - -pander(df) - -``` - - -## ToxCast, Water Samples: Detection Levels - -As an initial exploration of limitations of using ToxCast with the water sample data, ToxCast endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level for the endpoint with the minimum AC50 for that chemical is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "waterSamples.RData") -load(file=filePath) - -waterSamples$site["USGS-04157005" == waterSamples$site] <- "USGS-04157000" - - -pCodeSummary <- select(pCodeInfo, srsname, casrn, parameter_units, mlWt) - -detectionLimits <- waterSamples[,grep("detectionLimit", names(waterSamples))] -detectionLimits <- na.omit(detectionLimits) - -detLevels <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue,-class, -minDetLevel,-chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## ToxCast, Water Samples: Chemical Summary Tables - -This table focuses on the individual compounds and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} - -datatable(chemSum2[,-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) -``` - -### ToxCast, Water Samples: Individual EndPoints -This table focuses on the individual endpoint/compound combinations and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r message=FALSE, results='asis', echo=FALSE} - - -chemSum3 <- chemicalSummary %>% - group_by(chnm, class, site, endPoint) %>% - summarize(hits=as.numeric(any(hits > 0)), - maxEAR=max(EAR)) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits), - maxEAR=max(maxEAR)) %>% - rename(assay_component_endpoint_name=endPoint) %>% - data.table() %>% - left_join(data.table(endPointInfo), by="assay_component_endpoint_name") %>% - select(chnm, maxEAR, freq, nSites, - endPoint=assay_component_endpoint_name, class, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(chemSum3[,-4]), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -endpointSummary <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -endpointSummary <- endpointSummary %>% - select(endPoint, maxEAR, freq, nSites, - endPoint, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(endpointSummary), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("End Point","Maximum EAR","Fraction of Sites with Hits","nSites","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -``` - -## ToxCast, Water Samples: Site Summaries - -This table focuses on the individual sites and the prevalence of potential adverse biological effects (`r length(unique(chemSum2$chnm))` total chemicals included in ToxCast). The table can be sorted by the fraction of samples with hits, number of chemicals with hits, number of endpoints with hits, maximum EAR, and land cover attributes to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -summary_display <- left_join(summary, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display, rownames = FALSE, - colnames=c("Station Name","Fraction of Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) -``` - -## ToxCast, Water Sample: Boxplots by Site -This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits, number of chemicals with hits, and the total number of collected samples is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -siteLimits <- filter(summary_display, freq>0) %>% - arrange(desc(nChem), desc(nEndPoints)) %>% - select(site,nEndPoints,nChem, nSamples) - - -summary_display2 <- chemicalSummary %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sToxWS <- ggplot(summary_display2, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$site) + - scale_y_log10(limits=c(0.03,5000)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.07, - label=siteLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.045, - label=siteLimits$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.03, - label=siteLimits$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - - -g_sToxWS <- ggplotGrob(sToxWS) -g_sToxWS$layout$clip[g_sToxWS$layout$name=="panel"] <- "off" -grid.draw(g_sToxWS) - -``` - -## ToxCast, Water Sample: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits <- filter(chemSum2, freq>0) %>% - arrange(desc(freq),desc(nEndPoints)) %>% - select(chnm, nEndPoints, freq) %>% - mutate(freq=sprintf("%.0f",100*freq)) - -chemicalSummary_display <- chemicalSummary %>% - filter(EAR>=0.1) - -chemToxWS <- ggplot(chemicalSummary_display, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits$chnm) + - scale_y_log10(limits=c(0.045,5000)) + - labs(x = "Chemical Name")+ - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.07, - label=chemLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.045, - label=chemLimits$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.045), ymax = log10(0.045)) - -g_chemToxWS <- ggplotGrob(chemToxWS) -g_chemToxWS$layout$clip[g_chemToxWS$layout$name=="panel"] <- "off" -grid.draw(g_chemToxWS) - -``` - -# ToxCast, Passive Data {#toxPassive} - -Passive samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis. - -```{r echo=FALSE, eval=TRUE} -library(knitr) -library(pander) -# ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)") - -df <- data.frame(ps=ps, stringsAsFactors=FALSE) - -names(df) <- c("Passive Samples") - -pander(df) - -``` - - -## ToxCast, Passive: Detection Levels - -As an initial exploration of limitations of using ToxCast with the passive data, ToxCast endpoints were compared with detection levels (MQL) for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} - -detLevels_passive <- select(passiveData, Chemical, MQL, CAS, class) %>% - right_join(endPoint_passive, by=c("CAS"="casn")) %>% - select(-mlWt, -conversion, -Chemical, -CAS) %>% - gather(endPoint,endPointValue,-MQL,-chnm, -Units,-class) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=MQL/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel=MQL) %>% - arrange(desc(EAR)) - - -datatable(detLevels_passive, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## ToxCast, Passive: Chemical Summary Tables - -This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), and number of endpoints with hits to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -chemSum2_passive_dt <- chemSum2_passive[,-6:-7] %>% - filter(freq > 0) - -datatable(chemSum2_passive_dt, rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits")) %>% - formatRound(c("maxEAR", "freq"), digits = 4) - -``` - -### ToxCast, Passive: Individual EndPoints -This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r message=FALSE, results='asis', echo=FALSE} - - -chemSum3_passive <- chemicalSummary_passive %>% -# group_by(chnm, class, site, endPoint) %>% -# summarize(hits= as.numeric(any(EAR > 0.1))) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits)) - -chemSum4_passive <- chemicalSummary_passive %>% - group_by(chnm, class, endPoint) %>% - summarize(maxEAR=max(EAR), - nSamples=1) %>% - left_join(chemSum3_passive, by=c("chnm","class","endPoint")) %>% - select(chnm, class, freq, maxEAR, nSamples, endPoint) %>% - left_join(endPointInfo, by=c("endPoint"="assay_component_endpoint_name")) %>% - select(chnm, maxEAR, freq, endPoint, class, contains("intended_target_")) %>% - rename(type=intended_target_type, - type_sub=intended_target_type_sub, - family=intended_target_family, - family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) %>% - filter(freq > 0) - - - datatable(distinct(chemSum4_passive), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - -``` - -## ToxCast, Passive: Site Summaries - -This table focuses on the individual sites, and the prevalence of potential adverse biological effects (`r length(unique(chemSum2_passive$chnm))` total chemicals included in ToxCast). The table can be sorted by number of chemicals with hits, number of endpoints with hits, maximum exposure:activity ratio (EAR), and land cover attributes to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -summary_display_passive <- left_join(summ1_passive, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -summary_display_passive <- summary_display_passive[,c(-2,-3)] -datatable(summary_display_passive, rownames = FALSE, - colnames=c("Station Name", "Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR", "Ag [%]", "Urban [%]")) %>% -# options = list(pageLength = 50)) %>% - formatRound(c("maxEAR"), digits = 2) -``` - -## ToxCast, Passive: Boxplots by Sites - -This figure displays ranges of exposure:activity ratio (EAR) values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -summary_display1_passive <- transform(summary_display_passive, - site = reorder(site, order(nChem,decreasing=TRUE))) - -siteLimits_passive <- filter(summary_display_passive, nChem>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem) - -summary_display2_passive <- chemicalSummary_passive %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sp <- ggplot(summary_display2_passive, aes(x=site, y=EAR)) + - geom_point() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - ylim(-1,10) + - scale_x_discrete(limits=siteLimits_passive$site)+ - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-0.5, label=siteLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-1, label=siteLimits_passive$nChem),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -1, ymax = -1) - -g_sp <- ggplotGrob(sp) -g_sp$layout$clip[g_sp$layout$name=="panel"] <- "off" -grid.draw(g_sp) - - -``` - - -## ToxCast, Passive: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits_passive <- filter(chemSum2_passive, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq=sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, nSites) - -chemicalSummary_display_passive <- chemicalSummary_passive %>% - filter(EAR>=0.1) - -cp <- ggplot(chemicalSummary_display_passive, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - ylim(-1,10) + - scale_x_discrete(limits=chemLimits_passive$chnm) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-0.5, - label=chemLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-1, - label=chemLimits_passive$nSites),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Sites:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -1, ymax = -1) - - -g_cp <- ggplotGrob(cp) -g_cp$layout$clip[g_cp$layout$name=="panel"] <- "off" -grid.draw(g_cp) - -``` - - -# Water Quality Guidelines, Water Samples {#WQGws} - -## Water Quality Guidelines, Water Samples: Detection Levels - -As an initial exploration of limitations of using water quality guidelines with the water sample data, water quality guidelines endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} - -detLevels_BM <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint_bm, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn) %>% - gather(endPoint,endPointValue,-class, -minDetLevel,-chnm,-Units) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels_BM, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## Water Quality Guidelines, Water Samples: Chemical Summary Tables - -This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - - -```{r, echo=FALSE, results='asis'} - -datatable(chemSum2_BM[-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) -``` - -## Water Quality Guidelines, Water Samples: Site Summaries - -This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the water quality benchmark endpoints to evaluate results based on different priorities."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - - -```{r, echo=FALSE, results='asis'} -summary_display_BM <- left_join(summary_BM, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display_BM, rownames = FALSE, - colnames=c("Station Name","Fraction Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) -``` - - -## Water Quality Guidelines, Water Samples: Boxplots by Site - -This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -siteLimits_BM <- filter(summary_display_BM, freq>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem,nSamples) - -summary_display2_BM <- chemicalSummary_BM %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - - -sBenchWS <- ggplot(summary_display2_BM, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits_BM$site) + - scale_y_log10(limits=c(0.03,250)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.07, - label=siteLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.045, - label=siteLimits_BM$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.03, - label=siteLimits_BM$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - -g_sBenchWS <- ggplotGrob(sBenchWS) -g_sBenchWS$layout$clip[g_sBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_sBenchWS) - - -``` - -## Water Quality Guidelines, Water Samples: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits_BM <- filter(chemSum2_BM, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq = sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, freq) - -chemicalSummary_display_BM <- chemicalSummary_BM %>% - filter(EAR>=0.1) - -cBenchWS <- ggplot(chemicalSummary_display_BM, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits_BM$chnm) + - scale_y_log10(limits=c(0.045,250)) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.07, - label=chemLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.045, - label=chemLimits_BM$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.045), ymax = log10(0.045)) - -g_cBenchWS <- ggplotGrob(cBenchWS) -g_cBenchWS$layout$clip[g_cBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_cBenchWS) -``` - - -# Comparisons - -This table is a comparison of the three different bio-effect evaluations (ToxCast with water samples, ToxCast with passive samples, water quality guidelines with water samples). The three classes that most commonly have potential adverse effects are highlighted (PAHs, pharmaceuticals, and pesticides). - -```{r echo=FALSE} -# ToxCast Water Samples: -toxWS <- chemSum2 %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm,class,freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive <- chemSum2_passive %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive$Class[toxPassive$Class == "PAHs"] <- "PAH" - -tradWS <- chemSum2_BM %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -tradWS <- tradWS[1:20,1:2] -toxPassive <- toxPassive[1:20,1:2] -toxWS <- toxWS[1:20,1:2] - -combo <- cbind(toxWS, toxPassive, tradWS) -names(combo) <- c("ToxCast-Water Samples: Chemical", "ToxCast-Water Samples: Class","ToxCast-Passive: Chemical", "ToxCast-Passive: Class","WQG-Water Samples: Chemical", "WQG-Water Samples: Class") -# emphasize.strong.cells(which(combo == "PAH", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, style = 'simple', split.table = Inf) - - -``` - - -```{r, echo=FALSE, results='asis'} -formattable(combo, list( - 'ToxCast-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'ToxCast-Passive: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'WQG-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))) -)) - -# emphasize.strong.cells(which(combo == "Herbicide" | combo == "Insecticide", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, split.table = Inf) -``` - - -# Maps {#maps} - -## ToxCast, Water Samples: Map -This map summarizes the water sample ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-19) - -```{r, echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5} -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapData <- left_join(stationINFO, summary, by=c("shortName"="site")) -mapData <- mapData[!is.na(mapData$dec.lat.va),] -mapData <- mapData[!is.na(mapData$nChem),] - - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,5,10,100,1000,2500)#seq(0,2500, 500) # This is maxEAR - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(5000,15000, 500) -mapData$sizes <- rad[as.numeric(cut(mapData$nChem, c(-1:19)))] - -pal = colorBin(col_types, mapData$maxEAR, bins = leg_vals) - -m = leaflet(mapData) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0('',mapData$Station.Name,"
", - "', - "', - "', - "', - "
Frequency",sprintf("%1.1f",mapData$freq),'
nSample",mapData$nSamples,'
maxEAR",sprintf("%1.1f",mapData$maxEAR),'
nChem",mapData$nChem,'
nEndPoints",mapData$nEndPoints,'
') - , - fillColor = ~pal(maxEAR), - weight = 1, - color = "black", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, - opacity = 0.8, - title = 'Maximum EAR') - -m - -``` - -## ToxCast, Passive: Map -This map summarizes the passive ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-3) - -```{r, echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5} - -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapDataPassive <- left_join(stationINFO, summ1_passive, by=c("shortName"="site")) -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$dec.lat.va),] -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,2,3,5,7,9)#seq(0,2500, 500) # This is maxEAR scale - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(2500,15000, 2500) -mapDataPassive$sizes <- rad[as.numeric(cut(mapDataPassive$nChem, c(-1,0,1,2,3)))] -mapDataPassive$sizes[is.na(mapDataPassive$sizes)] <- 1000 - -pal = colorBin(col_types, mapDataPassive$maxEAR, bins = leg_vals) - - -map2 = leaflet(mapDataPassive) %>% -# addProviderTiles("Hydda.Full") %>% # There are more maybe worth looking at - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0("",mapDataPassive$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f",mapDataPassive$maxEAR),'
nChem",mapDataPassive$nChem,'
nEndPoints",mapDataPassive$nEndPoints,'
'), - fillColor = ~pal(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map2 - -``` - - -## Water Quality Guidelines, Water Samples: Map -This map summarizes the passive water quality guideline results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-10) - -```{r echo=FALSE, results='asis', fig.width=7, fig.height=5} -mapDataWQ <- left_join(stationINFO, summary_BM, by=c("shortName"="site")) -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$dec.lat.va),] -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals_BM <- c(0,1,25,50,75,100,125)#seq(0,2500, 500) # This is maxEAR scale - -colsWQ <- colorNumeric(col_types, domain = leg_vals_BM) -radWQ <- seq(2500,15000, 2500) -mapDataWQ$sizes <- rad[as.numeric(cut(mapDataWQ$nChem, c(-1,0,1,5,10)))] -mapDataWQ$sizes[is.na(mapDataWQ$sizes)] <- 1000 - -palWQ = colorBin(col_types, mapDataWQ$maxEAR, bins = leg_vals_BM) - - -map4 = leaflet(mapDataWQ) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup=paste0("",mapDataWQ$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f", mapDataWQ$maxEAR),'
nChem",mapDataWQ$nChem,'
nEndPoints", mapDataWQ$nEndPoints,'
'), - fillColor = ~palWQ(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map4 - -``` - - - - - diff --git a/inst/doc/SummaryToxCast.html b/inst/doc/SummaryToxCast.html deleted file mode 100644 index 8fe03539..00000000 --- a/inst/doc/SummaryToxCast.html +++ /dev/null @@ -1,568 +0,0 @@ - - - - - - - - - - - - - -Assessment of Potential Biological Effects in Great Lakes Tributaries Using ToxCast with Comparisons to Assessment Using Water Quality Guidelines. - - - - - - - - - - - - - - - - - - - - - - - - -

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1 Introduction

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1.1 Screening Endpoints Used in Analysis

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  • ToxCast: (EPA NCCT) -
      -
    • “High throughput screening assays” -
        -
      • In-vitro Exposures to living cells or isolated proteins
      • -
      • Screens for potential adverse biological effects
      • -
      • Much is focused on gaining information on biological pathways
      • -
    • -
    • 1860 compounds
    • -
    • 821 endpoints
    • -
    • AC50 used for this analysis (concentration at which activity is 50% of its maximum)
    • -
    • Exposure:Activity Ratio (EAR) = concentration / AC50
    • -
  • -
  • Established Water quality guidelines -
      -
    • Water sample analysis (not complete for passive samplers yet) -
        -
      • USEPA
      • -
      • Canadian Council of Ministers of the Environment
      • -
      • USGS
      • -
      • Literature
      • -
    • -
  • -
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1.2 Matches of Screening Endpoints

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  • Which chemicals are included in ToxCast and Water Quality Guideline assessments? -
      -
    • Water samples -
        -
      • 39 compounds of 62 total
      • -
      • Herbicide, Pharmaceuticals, Flavor/fragrance, PAH, Plasticizer, Insecticide, Other, Solvent, Fire Retardant, Antioxidant, Detergent Metabolites, Fuel, Antimicrobial Disinfectant
      • -
    • -
    • Passive samplers -
        -
      • 51 compounds of 162 total
      • -
      • PAHs, Pharmaceuticals, Other, Detergent metabolites, Flavor/Fragrance, Herbicide, Insecticide, OC Pesticides, Plasticizer, Solvent, Antimicrobial disinfectant
      • -
    • -
  • -
  • Water Quality Guidelines -
      -
    • Water samples -
        -
      • 24 compounds of 62 total
      • -
      • PAH, Herbicide, Insecticide, Fuel, Plasticizer, Solvent, Other
      • -
    • -
  • -
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2 ToxCast, Water Sample Data

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Water samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis.

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Water Samples: Organic Waste Compounds
PAH (6)
Insecticides (6)
Herbicides (7)
Fire retardants (4)
Pharmaceuticals (3)
Plasticizers (5)
Detergent metabolites (8)
Antimicrobial disinfectants (3)
Solvents (2)
Fuels (4)
Dye/pigments (1)
Flavors & fragrances (10)
Sterols (4)
Misc (3)
-
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2.1 ToxCast, Water Samples: Detection Levels

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As an initial exploration of limitations of using ToxCast with the water sample data, ToxCast endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level for the endpoint with the minimum AC50 for that chemical is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included.

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2.2 ToxCast, Water Samples: Chemical Summary Tables

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This table focuses on the individual compounds and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

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2.2.1 ToxCast, Water Samples: Individual EndPoints

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This table focuses on the individual endpoint/compound combinations and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

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2.3 ToxCast, Water Samples: Site Summaries

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This table focuses on the individual sites and the prevalence of potential adverse biological effects (39 total chemicals included in ToxCast). The table can be sorted by the fraction of samples with hits, number of chemicals with hits, number of endpoints with hits, maximum EAR, and land cover attributes to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

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2.4 ToxCast, Water Sample: Boxplots by Site

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This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits, number of chemicals with hits, and the total number of collected samples is included. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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2.5 ToxCast, Water Sample: Boxplots by Chemical

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This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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3 ToxCast, Passive Data

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Passive samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis.

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Passive Samples
PAH (33)
Organic Waste Compounds (53)
Organochlorine Pesticides (32)
PBDEs (5)
Pharmaceuticals (31)
PCB (sum of total)
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3.1 ToxCast, Passive: Detection Levels

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As an initial exploration of limitations of using ToxCast with the passive data, ToxCast endpoints were compared with detection levels (MQL) for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included.

-

-

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-
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3.2 ToxCast, Passive: Chemical Summary Tables

-

This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), and number of endpoints with hits to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

-

-

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3.2.1 ToxCast, Passive: Individual EndPoints

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This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

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3.3 ToxCast, Passive: Site Summaries

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This table focuses on the individual sites, and the prevalence of potential adverse biological effects (51 total chemicals included in ToxCast). The table can be sorted by number of chemicals with hits, number of endpoints with hits, maximum exposure:activity ratio (EAR), and land cover attributes to evaluate results based on different priorities. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

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3.4 ToxCast, Passive: Boxplots by Sites

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This figure displays ranges of exposure:activity ratio (EAR) values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included.“Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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- - -
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3.5 ToxCast, Passive: Boxplots by Chemical

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This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included.“Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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4 Water Quality Guidelines, Water Samples

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4.1 Water Quality Guidelines, Water Samples: Detection Levels

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As an initial exploration of limitations of using water quality guidelines with the water sample data, water quality guidelines endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included.

-

-

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-
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4.2 Water Quality Guidelines, Water Samples: Chemical Summary Tables

-

This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities.“Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

-

-

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-
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4.3 Water Quality Guidelines, Water Samples: Site Summaries

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This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the water quality benchmark endpoints to evaluate results based on different priorities.“Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater.

-

-

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4.4 Water Quality Guidelines, Water Samples: Boxplots by Site

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This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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- - -
-
-
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4.5 Water Quality Guidelines, Water Samples: Boxplots by Chemical

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This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. “Hits” are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included.

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5 Comparisons

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This table is a comparison of the three different bio-effect evaluations (ToxCast with water samples, ToxCast with passive samples, water quality guidelines with water samples). The three classes that most commonly have potential adverse effects are highlighted (PAHs, pharmaceuticals, and pesticides).

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
ToxCast-Water Samples: ChemicalToxCast-Water Samples: ClassToxCast-Passive: ChemicalToxCast-Passive: ClassWQG-Water Samples: ChemicalWQG-Water Samples: Class
MetolachlorHerbicideFluorenePAHFluoranthenePAH
AtrazineHerbicideAspirinPharmaceuticalsPyrenePAH
CaffeinePharmaceuticalsErythromycinPharmaceuticalsBenzo[a]pyrenePAH
BenzophenoneFlavor/fragranceNaphthalenePAHAtrazineHerbicide
NaphthalenePAHGemfibrozilPharmaceuticalsAnthracenePAH
Diethyl phthalatePlasticizerNACarbarylInsecticide
CotininePharmaceuticalsNAMetolachlorHerbicide
Triphenyl phosphatePlasticizerNAPhenanthrenePAH
CarbarylInsecticideNADichlorvosInsecticide
BromacilHerbicideNANaphthalenePAH
1,4-DichlorobenzeneOtherNAPentachlorophenolHerbicide
IsophoroneSolventNANA
Methyl salicylateOtherNANA
Tris(2-butoxyethyl) phosphateFire RetardantNANA
DichlorvosInsecticideNANA
FluoranthenePAHNANA
PhenanthrenePAHNANA
Tributyl phosphateFire RetardantNANA
dl-MentholPharmaceuticalsNANA
PyrenePAHNANA
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6 Maps

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6.1 ToxCast, Water Samples: Map

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This map summarizes the water sample ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points.

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Color: Maximum EAR
Size: Number of chemicals with hits (0-19)

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-

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6.2 ToxCast, Passive: Map

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This map summarizes the passive ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points.

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Color: Maximum EAR
Size: Number of chemicals with hits (0-3)

-

-

-
-
-

6.3 Water Quality Guidelines, Water Samples: Map

-

This map summarizes the passive water quality guideline results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points.

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Color: Maximum EAR
Size: Number of chemicals with hits (0-10)

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- - - - - - - - diff --git a/inst/doc/endPointExploration.R b/inst/doc/endPointExploration.R deleted file mode 100644 index 894a2dde..00000000 --- a/inst/doc/endPointExploration.R +++ /dev/null @@ -1,108 +0,0 @@ -## ----message=FALSE, echo=TRUE, results='asis'---------------------------- -library(toxEval) -library(DT) -library(dplyr) -library(tidyr) - -wData <- wData -pCodeInfo <- pCodeInfo - -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) - -endPoint <- endPointToxCreate(pCodeInfo) -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -endPointInfo <- endPointInfo -# epSumm <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -siteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) -summary <- siteSumm(chemicalSummary,siteKey) - - -## ------------------------------------------------------------------------ -group <- "transcription factor" -groupCol <- "intended_target_type_sub" -chemicalSummary.site <- "site" -chemicalSummary.Key <- "endPoint" -chemicalSummary.Date <- "date" -funcToSummerise <- "sumEAR" - -endPointInfoSub <- select_(endPointInfo, "assay_component_endpoint_name", groupCol) %>% - unique() - -chemicalSummary <- chemicalSummary %>% - filter(endPoint %in% endPointInfoSub$assay_component_endpoint_name ) %>% - left_join(endPointInfoSub, - by=c("endPoint"="assay_component_endpoint_name")) - -groupSumm <- chemicalSummary %>% - group_by(site) %>% - summarise(nChem = length(unique(chnm)), - nEndPoints = length(unique(endPoint))) %>% - select(nChem,nEndPoints) %>% - mutate(nChem = median(nChem), - nEndPoints = median(nEndPoints)) %>% - unique() - -endpointSummary <- chemicalSummary %>% - filter_(paste0(groupCol," == '", group, "'")) %>% - select_("hits","EAR","endPoint", - chemicalSummary.site,chemicalSummary.Date,groupCol) %>% - group_by_(chemicalSummary.site, chemicalSummary.Date) %>% - summarise(sumEAR = sum(EAR), - nHits = sum(hits)) - -statsOfSum <- endpointSummary%>% - group_by_(chemicalSummary.site) %>% - summarise_(meanEAR = paste0("mean(",funcToSummerise,")"), - # medianEAR = paste0("median(",funcToSummerise,")"), - maxEAR = paste0("max(",funcToSummerise,")"), - sumHits = "sum(nHits)", - nSamples = "n()")%>% - data.frame()%>% - mutate(site = siteKey[site]) - - - - - -datatable(statsOfSum, rownames = FALSE, - caption=paste("Summary of", funcToSummerise, "of",group)) %>% - formatRound(c("meanEAR","maxEAR","sumHits","nSamples"), - digits = 1) - - - -## ----fig.width=7, fig.height=7------------------------------------------- -library(ggplot2) - -siteLimits <- stationINFO %>% - mutate(lakeCat = factor(Lake, - levels=c("Lake Superior","Lake Michigan", - "Lake Huron", "St. Lawrence River", - "Detroit River and Lake St. Clair","Lake Erie","Lake Ontario"))) %>% - arrange(lakeCat) %>% - mutate(lakeColor = c("red","black","green","brown","brown","brown","blue")[as.numeric(lakeCat)] ) %>% - filter(fullSiteID %in% unique(endpointSummary$site)) - - -endPointSummBP <- endpointSummary %>% - data.frame()%>% - mutate(site = siteKey[site]) %>% - mutate(site = factor(site, levels=siteLimits$Station.shortname)) - -sToxWS <- ggplot(endPointSummBP, aes(x=site, y=sumEAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25, colour=siteLimits$lakeColor), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$Station.shortname) + - # scale_y_log10(limits=c(0.03,5000)) + - # labs(x = "Site") + - geom_text(data=data.frame(), aes(x=c(5, 18,31,45,56), - y=-.5, label=c("Superior","Michigan","Huron","Erie","Ontario")), - colour=factor(c("red","black","green","brown","blue"), - levels=c("red","black","green","brown","blue")), size=3) - -sToxWS - diff --git a/inst/doc/endPointExploration.Rmd b/inst/doc/endPointExploration.Rmd deleted file mode 100644 index 83d73433..00000000 --- a/inst/doc/endPointExploration.Rmd +++ /dev/null @@ -1,127 +0,0 @@ ---- -title: "EndpointExploration" -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{ToxEval Summary} - \usepackage[utf8]{inputenc} ---- - -```{r message=FALSE, echo=TRUE, results='asis'} -library(toxEval) -library(DT) -library(dplyr) -library(tidyr) - -wData <- wData -pCodeInfo <- pCodeInfo - -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) - -endPoint <- endPointToxCreate(pCodeInfo) -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -endPointInfo <- endPointInfo -# epSumm <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -siteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) -summary <- siteSumm(chemicalSummary,siteKey) - -``` - - -```{r } -group <- "transcription factor" -groupCol <- "intended_target_type_sub" -chemicalSummary.site <- "site" -chemicalSummary.Key <- "endPoint" -chemicalSummary.Date <- "date" -funcToSummerise <- "sumEAR" - -endPointInfoSub <- select_(endPointInfo, "assay_component_endpoint_name", groupCol) %>% - unique() - -chemicalSummary <- chemicalSummary %>% - filter(endPoint %in% endPointInfoSub$assay_component_endpoint_name ) %>% - left_join(endPointInfoSub, - by=c("endPoint"="assay_component_endpoint_name")) - -groupSumm <- chemicalSummary %>% - group_by(site) %>% - summarise(nChem = length(unique(chnm)), - nEndPoints = length(unique(endPoint))) %>% - select(nChem,nEndPoints) %>% - mutate(nChem = median(nChem), - nEndPoints = median(nEndPoints)) %>% - unique() - -endpointSummary <- chemicalSummary %>% - filter_(paste0(groupCol," == '", group, "'")) %>% - select_("hits","EAR","endPoint", - chemicalSummary.site,chemicalSummary.Date,groupCol) %>% - group_by_(chemicalSummary.site, chemicalSummary.Date) %>% - summarise(sumEAR = sum(EAR), - nHits = sum(hits)) - -statsOfSum <- endpointSummary%>% - group_by_(chemicalSummary.site) %>% - summarise_(meanEAR = paste0("mean(",funcToSummerise,")"), - # medianEAR = paste0("median(",funcToSummerise,")"), - maxEAR = paste0("max(",funcToSummerise,")"), - sumHits = "sum(nHits)", - nSamples = "n()")%>% - data.frame()%>% - mutate(site = siteKey[site]) - - - - - -datatable(statsOfSum, rownames = FALSE, - caption=paste("Summary of", funcToSummerise, "of",group)) %>% - formatRound(c("meanEAR","maxEAR","sumHits","nSamples"), - digits = 1) - - -``` - - -```{r fig.width=7, fig.height=7,} -library(ggplot2) - -siteLimits <- stationINFO %>% - mutate(lakeCat = factor(Lake, - levels=c("Lake Superior","Lake Michigan", - "Lake Huron", "St. Lawrence River", - "Detroit River and Lake St. Clair","Lake Erie","Lake Ontario"))) %>% - arrange(lakeCat) %>% - mutate(lakeColor = c("red","black","green","brown","brown","brown","blue")[as.numeric(lakeCat)] ) %>% - filter(fullSiteID %in% unique(endpointSummary$site)) - - -endPointSummBP <- endpointSummary %>% - data.frame()%>% - mutate(site = siteKey[site]) %>% - mutate(site = factor(site, levels=siteLimits$Station.shortname)) - -sToxWS <- ggplot(endPointSummBP, aes(x=site, y=sumEAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25, colour=siteLimits$lakeColor), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$Station.shortname) + - # scale_y_log10(limits=c(0.03,5000)) + - # labs(x = "Site") + - geom_text(data=data.frame(), aes(x=c(5, 18,31,45,56), - y=-.5, label=c("Superior","Michigan","Huron","Erie","Ontario")), - colour=factor(c("red","black","green","brown","blue"), - levels=c("red","black","green","brown","blue")), size=3) - -sToxWS -``` diff --git a/inst/doc/endPointExploration.html b/inst/doc/endPointExploration.html deleted file mode 100644 index 7e8c0eee..00000000 --- a/inst/doc/endPointExploration.html +++ /dev/null @@ -1,185 +0,0 @@ - - - - - - - - - - - - - -EndpointExploration - - - - - - - - - - - - - - - - - - - - - - - - - -
library(toxEval)
-library(DT)
-library(dplyr)
-library(tidyr)
-
-wData <- wData
-pCodeInfo <- pCodeInfo
-
-packagePath <- system.file("extdata", package="toxEval")
-filePath <- file.path(packagePath, "stationINFO.RData")
-load(file=filePath)
-
-endPoint <- endPointToxCreate(pCodeInfo)
-chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint)
-endPointInfo <- endPointInfo
-# epSumm <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo)
-
-siteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID)
-summary <- siteSumm(chemicalSummary,siteKey)
-
group <- "transcription factor"
-groupCol <- "intended_target_type_sub"
-chemicalSummary.site <- "site"
-chemicalSummary.Key <- "endPoint"
-chemicalSummary.Date <- "date"
-funcToSummerise <- "sumEAR"
-
-endPointInfoSub <- select_(endPointInfo, "assay_component_endpoint_name", groupCol) %>%
-  unique()
-
-chemicalSummary <- chemicalSummary %>%
-  filter(endPoint %in% endPointInfoSub$assay_component_endpoint_name ) %>%
-  left_join(endPointInfoSub,
-            by=c("endPoint"="assay_component_endpoint_name"))
-
-groupSumm <- chemicalSummary %>%
-  group_by(site) %>%
-  summarise(nChem = length(unique(chnm)),
-            nEndPoints = length(unique(endPoint))) %>%
-      select(nChem,nEndPoints) %>%
-      mutate(nChem = median(nChem),
-             nEndPoints = median(nEndPoints)) %>%
-      unique()
-
-endpointSummary <- chemicalSummary %>%
-  filter_(paste0(groupCol," == '", group, "'")) %>%
-  select_("hits","EAR","endPoint",
-          chemicalSummary.site,chemicalSummary.Date,groupCol) %>%
-  group_by_(chemicalSummary.site, chemicalSummary.Date) %>%
-  summarise(sumEAR = sum(EAR),
-            nHits = sum(hits)) 
-
-statsOfSum <- endpointSummary%>%
-  group_by_(chemicalSummary.site) %>%
-  summarise_(meanEAR = paste0("mean(",funcToSummerise,")"),
-             # medianEAR = paste0("median(",funcToSummerise,")"),
-             maxEAR = paste0("max(",funcToSummerise,")"),
-             sumHits = "sum(nHits)",
-             nSamples = "n()")%>%
-  data.frame()%>%
-  mutate(site = siteKey[site])
-  
-
-
-
-
-datatable(statsOfSum, rownames = FALSE, 
-          caption=paste("Summary of", funcToSummerise, "of",group))  %>% 
-    formatRound(c("meanEAR","maxEAR","sumHits","nSamples"), 
-                digits = 1)
-

-

-
library(ggplot2)
-
-siteLimits <- stationINFO %>%
-  mutate(lakeCat = factor(Lake, 
-            levels=c("Lake Superior","Lake Michigan",
-                     "Lake Huron", "St. Lawrence River",
-                     "Detroit River and Lake St. Clair","Lake Erie","Lake Ontario"))) %>%
-  arrange(lakeCat) %>%
-  mutate(lakeColor = c("red","black","green","brown","brown","brown","blue")[as.numeric(lakeCat)] ) %>%
-  filter(fullSiteID %in% unique(endpointSummary$site))
-  
-
-endPointSummBP <- endpointSummary %>%
-  data.frame()%>%
-  mutate(site = siteKey[site]) %>%
-  mutate(site = factor(site, levels=siteLimits$Station.shortname)) 
-
-sToxWS <- ggplot(endPointSummBP, aes(x=site, y=sumEAR)) +
-  geom_boxplot() +
-  theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25, colour=siteLimits$lakeColor), 
-        legend.position = "none")+
-  scale_x_discrete(limits=siteLimits$Station.shortname) +
-  # scale_y_log10(limits=c(0.03,5000)) +
-  # labs(x = "Site")  +
-  geom_text(data=data.frame(), aes(x=c(5, 18,31,45,56),
-                                   y=-.5, label=c("Superior","Michigan","Huron","Erie","Ontario")),
-                                   colour=factor(c("red","black","green","brown","blue"),
-                                                 levels=c("red","black","green","brown","blue")), size=3) 
-
-sToxWS
-
- - -
- - - - - - - - diff --git a/inst/doc/siteTables.R b/inst/doc/siteTables.R deleted file mode 100644 index 3d0c28db..00000000 --- a/inst/doc/siteTables.R +++ /dev/null @@ -1,170 +0,0 @@ -## ----message=FALSE, echo=FALSE, results='asis',warning=FALSE------------- -library(dplyr) -library(tidyr) -library(DT) -library(toxEval) -library(knitr) - - -pCodeInfo <- pCodeInfo -wData <- wData -endPointInfo <- endPointInfo -# AC50 data provided in the toxEval package: -AC50gain <- AC50gain -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -endPoint <- endPointToxCreate(pCodeInfo) - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -unitConversion <- setNames(c(10^6, 10^3), c("pg/L", "ng/L") ) - -AC50_passive <- right_join(AC50gain[,c("casn"), drop=FALSE], - passiveData[,c("CAS", "Units", "mlWt","Chemical")], - by= c("casn" = "CAS")) %>% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) - -siteSummary <- siteSumm(chemicalSummary,newSiteKey) - -for(i in siteSummary$site){ - - chemSummSite <- filter(chemicalSummary, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_BM <- filter(chemicalSummary_BM, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_passive <- filter(chemicalSummary_passive, site == names(newSiteKey)[i == newSiteKey]) - - totalSamples <- select(chemSummSite,date,site) %>% - distinct()%>% - nrow() - - - chemSummSite2 <- select(chemSummSite,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_BM <- select(chemSummSite_BM,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_passive <- select(chemSummSite_passive,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite1 <- chemSumm(chemSummSite) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_BM <- chemSumm(chemSummSite_BM) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_BM, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_passive <- chemSumm(chemSummSite_passive) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_passive, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - names(chemSummSite1) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_BM) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_passive) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - cat("\n\n##", i, "\n") - cat("\n###ToxCast, Water Samples\n") - - if(nrow(chemSummSite1) > 0){ - print(kable(chemSummSite1, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###Water Quality Guidelines, Water Samples\n") - if(nrow(chemSummSite1_BM) > 0){ - print(kable(chemSummSite1_BM, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo Water Quality Guidelines, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###ToxCast, Passive\n") - if(nrow(chemSummSite1_passive) > 0){ - print(kable(chemSummSite1_passive, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Passive hits in 1 sample\n") - } -} - - diff --git a/inst/doc/siteTables.Rmd b/inst/doc/siteTables.Rmd deleted file mode 100644 index 97ae571d..00000000 --- a/inst/doc/siteTables.Rmd +++ /dev/null @@ -1,188 +0,0 @@ ---- -title: "Site Tables" -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes - toc_depth: 2 -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{Site Tables} - \usepackage[utf8]{inputenc} ---- - -# Site Tables - -```{r message=FALSE, echo=FALSE, results='asis',warning=FALSE} -library(dplyr) -library(tidyr) -library(DT) -library(toxEval) -library(knitr) - - -pCodeInfo <- pCodeInfo -wData <- wData -endPointInfo <- endPointInfo -# AC50 data provided in the toxEval package: -AC50gain <- AC50gain -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -endPoint <- endPointToxCreate(pCodeInfo) - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -unitConversion <- setNames(c(10^6, 10^3), c("pg/L", "ng/L") ) - -AC50_passive <- right_join(AC50gain[,c("casn"), drop=FALSE], - passiveData[,c("CAS", "Units", "mlWt","Chemical")], - by= c("casn" = "CAS")) %>% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) - -siteSummary <- siteSumm(chemicalSummary,newSiteKey) - -for(i in siteSummary$site){ - - chemSummSite <- filter(chemicalSummary, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_BM <- filter(chemicalSummary_BM, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_passive <- filter(chemicalSummary_passive, site == names(newSiteKey)[i == newSiteKey]) - - totalSamples <- select(chemSummSite,date,site) %>% - distinct()%>% - nrow() - - - chemSummSite2 <- select(chemSummSite,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_BM <- select(chemSummSite_BM,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_passive <- select(chemSummSite_passive,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite1 <- chemSumm(chemSummSite) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_BM <- chemSumm(chemSummSite_BM) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_BM, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_passive <- chemSumm(chemSummSite_passive) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_passive, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - names(chemSummSite1) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_BM) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_passive) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - cat("\n\n##", i, "\n") - cat("\n###ToxCast, Water Samples\n") - - if(nrow(chemSummSite1) > 0){ - print(kable(chemSummSite1, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###Water Quality Guidelines, Water Samples\n") - if(nrow(chemSummSite1_BM) > 0){ - print(kable(chemSummSite1_BM, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo Water Quality Guidelines, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###ToxCast, Passive\n") - if(nrow(chemSummSite1_passive) > 0){ - print(kable(chemSummSite1_passive, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Passive hits in 1 sample\n") - } -} - -``` \ No newline at end of file diff --git a/inst/doc/siteTables.html b/inst/doc/siteTables.html deleted file mode 100644 index 0a0548d8..00000000 --- a/inst/doc/siteTables.html +++ /dev/null @@ -1,5555 +0,0 @@ - - - - - - - - - - - - - -Site Tables - - - - - - - - - - - - - - - - -
-

1 Site Tables

-
-

1.1 Portage

-
-

1.1.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Portage
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide2082.3279640.953
AtrazineHerbicide74.35016640.750
NaphthalenePAH5.9717640.047
CotininePharmaceuticals5.2432620.032
CaffeinePharmaceuticals3.1472640.938
BenzophenoneFlavor/fragrance0.5811640.188
Diethyl phthalatePlasticizer0.2232640.031
Tris(2-butoxyethyl) phosphateFire Retardant0.1471640.016
-
-
-

1.1.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Portage
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide22.3333640.359
Benzo[a]pyrenePAH2.8573600.300
PyrenePAH2.8001600.700
FluoranthenePAH2.5001640.750
AnthracenePAH1.6671570.088
MetolachlorHerbicide0.7691640.094
CarbarylInsecticide0.1501640.016
-
-
-

1.1.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Portage
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
ErythromycinPharmaceuticals1.523211
FluorenePAHs0.345111
-
-
-
-

1.2 Maumee

-
-

1.2.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Maumee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide825.9906640.984
AtrazineHerbicide17.38511640.797
NaphthalenePAH5.1187640.156
CotininePharmaceuticals4.3692620.081
CaffeinePharmaceuticals1.4882640.688
1,4-DichlorobenzeneOther0.8681640.016
IsophoroneSolvent0.7291640.078
BenzophenoneFlavor/fragrance0.5081640.094
Tributyl phosphateFire Retardant0.2512640.016
Diethyl phthalatePlasticizer0.2232630.032
-
-
-

1.2.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Maumee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide5.2222640.484
Benzo[a]pyrenePAH2.1433610.148
PyrenePAH1.6001580.534
FluoranthenePAH1.2501600.550
AnthracenePAH0.8331640.016
MetolachlorHerbicide0.3051640.094
-
-
-

1.2.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Maumee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.119111
-
-
-
-

1.3 Raisin

-
-

1.3.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Raisin
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide607.3455440.795
AtrazineHerbicide5.9187440.432
CotininePharmaceuticals3.4952440.023
NaphthalenePAH3.4122440.023
CaffeinePharmaceuticals1.0872440.568
IsophoroneSolvent0.8492440.023
BenzophenoneFlavor/fragrance0.5811440.182
Bisphenol AAntioxidant0.2546440.386
Diethyl phthalatePlasticizer0.2232440.045
Tris(2-chloroethyl) phosphatePlasticizer0.1471440.023
-
-
-

1.3.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Raisin
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide1.7781440.205
PyrenePAH1.6001430.651
FluoranthenePAH1.5001420.667
Benzo[a]pyrenePAH1.4292410.244
MetolachlorHerbicide0.2241440.045
-
-
-

1.3.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Raisin
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.453111
FluorenePAHs0.149111
-
-
-
-

1.4 Manitowoc

-
-

1.4.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Manitowoc
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide534.4645430.837
NaphthalenePAH2.5592430.023
AtrazineHerbicide1.5545430.209
BenzophenoneFlavor/fragrance0.5811430.163
Diethyl phthalatePlasticizer0.2232430.023
-
-
-

1.4.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Manitowoc
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide0.4671430.093
PyrenePAH0.4001380.263
FluoranthenePAH0.2501400.175
MetolachlorHerbicide0.1971430.023
-
-
-

1.4.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.5 MilwaukeeMouth

-
-

1.5.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
MilwaukeeMouth
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide513.6415440.591
AtrazineHerbicide17.38511450.200
NaphthalenePAH3.4122450.111
dl-MentholPharmaceuticals2.0703450.022
CaffeinePharmaceuticals1.0872450.756
Diethyl phthalatePlasticizer0.6702450.200
BenzophenoneFlavor/fragrance0.6541450.378
Triphenyl phosphatePlasticizer0.2011450.022
BromacilHerbicide0.1912450.022
CarbarylInsecticide0.1631450.022
FluoranthenePAH0.1072450.022
PhenanthrenePAH0.1051450.022
-
-
-

1.5.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
MilwaukeeMouth
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH30.8001451.000
Benzo[a]pyrenePAH26.4293451.000
FluoranthenePAH26.0002451.000
AtrazineHerbicide5.2222450.111
AnthracenePAH5.0001410.805
PhenanthrenePAH1.3001450.444
CarbarylInsecticide0.2501450.044
MetolachlorHerbicide0.1901440.045
-
-
-

1.5.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.6 StJoseph

-
-

1.6.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StJoseph
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide395.6425240.792
AtrazineHerbicide7.3989250.320
CotininePharmaceuticals4.3692250.040
NaphthalenePAH1.7061250.080
CaffeinePharmaceuticals0.6872250.320
-
-
-

1.6.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StJoseph
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH14.8001240.917
Benzo[a]pyrenePAH13.5713240.625
FluoranthenePAH13.2501250.920
AnthracenePAH2.5001220.273
AtrazineHerbicide2.2221250.080
PhenanthrenePAH0.7001250.080
MetolachlorHerbicide0.1461240.042
-
-
-

1.6.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StJoseph
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
ErythromycinPharmaceuticals1.144211
AspirinPharmaceuticals0.267111
FluorenePAHs0.190111
-
-
-
-

1.7 Clinton

-
-

1.7.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Clinton
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide347.0555430.558
DichlorvosInsecticide132.1671430.372
NaphthalenePAH11.94210430.140
CotininePharmaceuticals6.9913430.140
AtrazineHerbicide3.6997430.233
CaffeinePharmaceuticals3.5472430.953
CarbarylInsecticide1.5013430.512
dl-MentholPharmaceuticals1.1042430.023
1,4-DichlorobenzeneOther0.8681430.093
BenzophenoneFlavor/fragrance0.5811430.442
FluoranthenePAH0.4056430.116
Triphenyl phosphatePlasticizer0.3521430.233
PhenanthrenePAH0.2922430.093
PyrenePAH0.2672430.070
Diethyl phthalatePlasticizer0.2232420.024
PrometonHerbicide0.2163430.047
Tris(2-butoxyethyl) phosphateFire Retardant0.1731430.116
BromacilHerbicide0.1631430.140
-
-
-

1.7.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Clinton
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH116.8002430.977
FluoranthenePAH98.7503430.977
Benzo[a]pyrenePAH78.5714430.930
DichlorvosInsecticide50.0002430.372
AnthracenePAH10.0001420.667
PhenanthrenePAH3.6252430.651
CarbarylInsecticide2.3004430.558
AtrazineHerbicide1.1111430.093
MetolachlorHerbicide0.1281430.023
NaphthalenePAH0.1271430.023
-
-
-

1.7.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Clinton
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.654111
AspirinPharmaceuticals0.572111
ErythromycinPharmaceuticals0.256211
-
-
-
-

1.8 Genesee

-
-

1.8.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Genesee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide249.8795140.929
AtrazineHerbicide1.8495140.286
CaffeinePharmaceuticals0.6872140.500
-
-
-

1.8.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Genesee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH2.4001140.929
FluoranthenePAH1.7501140.929
AnthracenePAH0.8331100.100
Benzo[a]pyrenePAH0.7142140.429
AtrazineHerbicide0.5561140.143
-
-
-

1.8.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.9 Saginaw

-
-

1.9.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Saginaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide152.7045310.839
NaphthalenePAH3.4122310.258
AtrazineHerbicide2.2195310.258
Methyl salicylateOther0.8031310.032
1,4-DichlorobenzeneOther0.7441310.065
CaffeinePharmaceuticals0.6872310.645
Triphenyl phosphatePlasticizer0.4532290.034
Diethyl phthalatePlasticizer0.4462310.065
BenzophenoneFlavor/fragrance0.3631310.065
CarbarylInsecticide0.3262310.032
-
-
-

1.9.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Saginaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH2.8573310.323
PyrenePAH2.4001300.800
FluoranthenePAH1.7501310.903
AnthracenePAH0.8331310.097
AtrazineHerbicide0.6671310.129
CarbarylInsecticide0.5003310.032
-
-
-

1.9.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Saginaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.415111
GemfibrozilPharmaceuticals0.295111
FluorenePAHs0.149111
-
-
-
-

1.10 HuronOH

-
-

1.10.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
HuronOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide124.940321.0
AtrazineHerbicide1.091421.0
CaffeinePharmaceuticals0.229220.5
BromacilHerbicide0.144120.5
-
-
-

1.10.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
HuronOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH0.400120.5
AtrazineHerbicide0.328121.0
FluoranthenePAH0.250120.5
-
-
-

1.10.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
HuronOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.892111
-
-
-
-

1.11 Vermilion

-
-

1.11.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Vermilion
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide121.469320.5
AtrazineHerbicide1.849521.0
-
-
-

1.11.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Vermilion
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide0.556121
-
-
-

1.11.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.12 BlackOH

-
-

1.12.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
BlackOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide90.234320.5
AtrazineHerbicide1.813521.0
CaffeinePharmaceuticals0.801221.0
Diethyl phthalatePlasticizer0.335220.5
Tributyl phosphateFire Retardant0.250220.5
-
-
-

1.12.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
BlackOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AnthracenePAH0.833120.5
PyrenePAH0.800120.5
FluoranthenePAH0.750120.5
Benzo[a]pyrenePAH0.714220.5
AtrazineHerbicide0.544120.5
-
-
-

1.12.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
BlackOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.577111
-
-
-
-

1.13 Rouge

-
-

1.13.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rouge
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
DichlorvosInsecticide68.3621430.209
MetolachlorHerbicide17.3531430.163
CotininePharmaceuticals6.9913430.093
NaphthalenePAH3.4122430.116
CaffeinePharmaceuticals2.2312430.953
1,4-DichlorobenzeneOther1.6122430.047
BenzophenoneFlavor/fragrance1.4524430.163
Diethyl phthalatePlasticizer1.0043430.163
CarbarylInsecticide0.4572430.512
4-(1,1,3,3-Tetramethylbutyl)phenolDetergent Metabolites0.3601410.244
Triphenyl phosphatePlasticizer0.3521430.163
FluoranthenePAH0.3166430.140
AtrazineHerbicide0.2771430.140
PhenanthrenePAH0.2742430.140
Tris(2-butoxyethyl) phosphateFire Retardant0.2651430.186
PyrenePAH0.2212430.093
Tris(2-chloroethyl) phosphatePlasticizer0.1151430.023
BromacilHerbicide0.1151430.023
-
-
-

1.13.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rouge
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH96.4294430.930
PyrenePAH96.4002430.953
FluoranthenePAH77.0003431.000
DichlorvosInsecticide25.8622430.209
AnthracenePAH11.6671420.786
PhenanthrenePAH3.4002430.744
CarbarylInsecticide0.7003430.535
-
-
-

1.13.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rouge
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs1.904111
AspirinPharmaceuticals1.106111
-
-
-
-

1.14 Sandusky

-
-

1.14.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Sandusky
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide58.999320.5
AtrazineHerbicide0.407321.0
-
-
-

1.14.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Sandusky
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AtrazineHerbicide0.122121
-
-
-

1.14.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.15 GrandMI

-
-

1.15.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
GrandMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide48.588320.5
AtrazineHerbicide0.370220.5
-
-
-

1.15.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
GrandMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH1.429220.5
PyrenePAH1.200120.5
FluoranthenePAH1.000120.5
AnthracenePAH0.833120.5
AtrazineHerbicide0.111120.5
-
-
-

1.15.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
GrandMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.327111
GemfibrozilPharmaceuticals0.270111
FluorenePAHs0.143111
-
-
-
-

1.16 Burns

-
-

1.16.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Burns
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide41.6472300.267
IsophoroneSolvent7.0505310.194
NaphthalenePAH4.2652310.710
AtrazineHerbicide1.8495310.323
CaffeinePharmaceuticals1.1442310.645
Diethyl phthalatePlasticizer0.5582310.290
BenzophenoneFlavor/fragrance0.3631310.387
Triphenyl phosphatePlasticizer0.3021300.067
Methyl salicylateOther0.2921310.032
CarbarylInsecticide0.1961310.032
BromacilHerbicide0.1631310.065
Tris(2-butoxyethyl) phosphateFire Retardant0.1331310.032
-
-
-

1.16.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Burns
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluoranthenePAH4.7501310.935
PyrenePAH4.0001310.968
Benzo[a]pyrenePAH2.1433310.581
AnthracenePAH1.6671300.200
AtrazineHerbicide0.5561310.161
CarbarylInsecticide0.3002310.065
PhenanthrenePAH0.2751310.161
-
-
-

1.16.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Burns
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.256111
NaphthalenePAHs0.222111
-
-
-
-

1.17 Cuyahoga

-
-

1.17.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Cuyahoga
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide38.1762270.222
DichlorvosInsecticide36.4601280.036
CotininePharmaceuticals6.9913280.143
CaffeinePharmaceuticals3.6052280.786
NaphthalenePAH2.5592280.321
dl-MentholPharmaceuticals1.2422280.036
BenzophenoneFlavor/fragrance0.7992280.464
AtrazineHerbicide0.4253280.179
Diethyl phthalatePlasticizer0.3352280.071
-
-
-

1.17.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Cuyahoga
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
DichlorvosInsecticide13.7932280.036
Benzo[a]pyrenePAH9.2863270.778
PyrenePAH7.6001280.929
FluoranthenePAH5.7501280.893
AnthracenePAH2.5001250.680
PhenanthrenePAH0.3001280.214
AtrazineHerbicide0.1281280.071
-
-
-

1.17.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Cuyahoga
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
ErythromycinPharmaceuticals1.686211
FluorenePAHs0.339111
-
-
-
-

1.18 GrandOH

-
-

1.18.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
GrandOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide27.764220.5
AtrazineHerbicide0.351221.0
-
-
-

1.18.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
GrandOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH0.400120.5
FluoranthenePAH0.250120.5
AtrazineHerbicide0.106120.5
-
-
-

1.18.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
GrandOH
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs1.011111
-
-
-
-

1.19 Oswego

-
-

1.19.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Oswego
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide17.3531260.808
CotininePharmaceuticals5.2432250.040
CaffeinePharmaceuticals0.6872260.808
Triphenyl phosphatePlasticizer0.5032250.040
BenzophenoneFlavor/fragrance0.3631260.077
Diethyl phthalatePlasticizer0.2232260.038
CarbarylInsecticide0.1961260.038
AtrazineHerbicide0.1481260.115
-
-
-

1.19.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Oswego
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH2.1433260.154
PyrenePAH0.8001210.333
FluoranthenePAH0.5001240.500
CarbarylInsecticide0.3002260.038
-
-
-

1.19.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Oswego
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.107111
-
-
-
-

1.20 BlackMI

-
-

1.20.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
BlackMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide13.882120.5
-
-
-

1.20.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.20.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
BlackMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.283111
FluorenePAHs0.101111
-
-
-
-

1.21 Fox

-
-

1.21.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Fox
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide13.882170.571
NaphthalenePAH6.824770.429
BenzophenoneFlavor/fragrance1.017270.571
Diethyl phthalatePlasticizer0.781370.429
Triphenyl phosphatePlasticizer0.352170.143
CaffeinePharmaceuticals0.229270.143
AtrazineHerbicide0.222170.571
-
-
-

1.21.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Fox
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH1.429270.571
PyrenePAH0.800171.000
FluoranthenePAH0.750171.000
-
-
-

1.21.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Fox
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.773111
NaphthalenePAHs0.469111
-
-
-
-

1.22 StLouis

-
-

1.22.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StLouis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
CotininePharmaceuticals11.3603310.032
MetolachlorHerbicide10.4121310.032
NaphthalenePAH3.4122310.355
PentachlorophenolHerbicide3.1964310.032
CarbarylInsecticide0.8483310.032
Triphenyl phosphatePlasticizer0.4021310.032
CaffeinePharmaceuticals0.4012310.194
IsophoroneSolvent0.3691310.032
Methyl salicylateOther0.3651310.032
BenzophenoneFlavor/fragrance0.3631310.065
Diethyl phthalatePlasticizer0.3352310.129
BromacilHerbicide0.2492310.032
AtrazineHerbicide0.1851310.032
2-tert-Butyl-4-methoxyphenolAntioxidant0.1211310.032
-
-
-

1.22.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StLouis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH2.1433310.032
CarbarylInsecticide1.3003310.032
PyrenePAH1.2001290.207
AnthracenePAH0.8331310.032
PentachlorophenolHerbicide0.5622310.032
FluoranthenePAH0.2501280.250
-
-
-

1.22.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
StLouis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.399111
-
-
-
-

1.23 Kalamazoo2

-
-

1.23.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Kalamazoo2
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide10.412111
-
-
-

1.23.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Kalamazoo2
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluoranthenePAH0.25111
-
-
-

1.23.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Kalamazoo2
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.268111
AspirinPharmaceuticals0.265111
-
-
-
-

1.24 Rocky

-
-

1.24.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rocky
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide10.412120.5
CotininePharmaceuticals4.369220.5
CaffeinePharmaceuticals1.144221.0
BenzophenoneFlavor/fragrance0.581120.5
AtrazineHerbicide0.240120.5
-
-
-

1.24.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rocky
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AnthracenePAH0.833120.5
FluoranthenePAH0.500120.5
PyrenePAH0.400120.5
-
-
-

1.24.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Rocky
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
ErythromycinPharmaceuticals1.575211
FluorenePAHs0.155111
-
-
-
-

1.25 IndianaHC

-
-

1.25.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IndianaHC
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide6.941120.5
NaphthalenePAH5.118720.5
CaffeinePharmaceuticals0.458220.5
AtrazineHerbicide0.277120.5
-
-
-

1.25.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IndianaHC
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH15.200121.0
Benzo[a]pyrenePAH7.857321.0
FluoranthenePAH6.000121.0
AnthracenePAH2.500121.0
PhenanthrenePAH0.150120.5
-
-
-

1.25.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
IndianaHC
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs8.924111
NaphthalenePAHs0.333111
-
-
-
-

1.26 PawPaw

-
-

1.26.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
PawPaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide6.941111
-
-
-

1.26.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
PawPaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH0.40111
FluoranthenePAH0.25111
-
-
-

1.26.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
PawPaw
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.425111
FluorenePAHs0.357111
-
-
-
-

1.27 Tonawanda

-
-

1.27.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Tonawanda
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
MetolachlorHerbicide6.941111
-
-
-

1.27.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Tonawanda
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluoranthenePAH0.25111
-
-
-

1.27.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.28 AuSable

-
-

1.28.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
AuSable
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
NaphthalenePAH5.1187260.038
Methyl salicylateOther0.8761260.269
Diethyl phthalatePlasticizer0.4462260.077
BenzophenoneFlavor/fragrance0.2901260.038
-
-
-

1.28.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 26 samples

-
-
-

1.28.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.29 Indian

-
-

1.29.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Indian
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
NaphthalenePAH5.118720.5
-
-
-

1.29.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.29.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Indian
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.476111
-
-
-
-

1.30 Menominee

-
-

1.30.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Menominee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
CotininePharmaceuticals3.4952400.025
BenzophenoneFlavor/fragrance2.0334400.350
1,4-DichlorobenzeneOther1.2402400.025
CaffeinePharmaceuticals0.2862400.025
Diethyl phthalatePlasticizer0.2232400.125
Tributyl phosphateFire Retardant0.2092400.025
Triphenyl phosphatePlasticizer0.2011400.025
-
-
-

1.30.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Menominee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.7142400.025
PyrenePAH0.4001380.079
FluoranthenePAH0.2501380.053
-
-
-

1.30.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.31 Cheboygan2

-
-

1.31.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Cheboygan2
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
NaphthalenePAH2.559220.5
CaffeinePharmaceuticals0.286220.5
-
-
-

1.31.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Cheboygan2
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.714220.5
-
-
-

1.31.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.32 StRegis

-
-

1.32.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
StRegis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Triphenyl phosphatePlasticizer0.6042160.312
-
-
-

1.32.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
StRegis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.7142160.062
FluoranthenePAH0.5001160.062
PyrenePAH0.4001160.062
-
-
-

1.32.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
StRegis
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.137111
-
-
-
-

1.33 Ontonagon

-
-

1.33.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Ontonagon
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
BenzophenoneFlavor/fragrance0.3631300.033
Triphenyl phosphatePlasticizer0.3521300.333
-
-
-

1.33.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Ontonagon
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH0.401290.034
FluoranthenePAH0.251300.067
-
-
-

1.33.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Ontonagon
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.315111
AspirinPharmaceuticals0.262111
NaphthalenePAHs0.196111
-
-
-
-

1.34 Cattaraugus

-
-

1.34.1 ToxCast, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Cattaraugus
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
CaffeinePharmaceuticals0.229211
-
-
-

1.34.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Cattaraugus
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH0.40111
FluoranthenePAH0.25111
-
-
-

1.34.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.35 Rifle

-
-

1.35.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.35.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.35.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Rifle
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.251111
-
-
-
-

1.36 HuronMI

-
-

1.36.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.36.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
HuronMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.714220.5
PyrenePAH0.400120.5
FluoranthenePAH0.250120.5
-
-
-

1.36.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
HuronMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.351111
-
-
-
-

1.37 Muskegon

-
-

1.37.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.37.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
Muskegon
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.714220.5
-
-
-

1.37.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Muskegon
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.194111
ErythromycinPharmaceuticals0.171211
-
-
-
-

1.38 Peshtigo

-
-

1.38.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.38.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Peshtigo
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
PyrenePAH1.6111
FluoranthenePAH1.5111
-
-
-

1.38.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.39 Sturgeon

-
-

1.39.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.39.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.39.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.40 Bad

-
-

1.40.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.40.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.40.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.41 BlackNY

-
-

1.41.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.41.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.41.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
BlackNY
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.184111
-
-
-
-

1.42 Escanaba

-
-

1.42.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.42.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.42.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.43 Ford

-
-

1.43.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.43.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.43.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.44 Grass

-
-

1.44.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.44.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.44.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Grass
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.119111
-
-
-
-

1.45 Manistee

-
-

1.45.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.45.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.45.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Manistee
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.274111
-
-
-
-

1.46 Manistique

-
-

1.46.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.46.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.46.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
Manistique
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
FluorenePAHs0.28111
-
-
-
-

1.47 Montreal

-
-

1.47.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.47.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.47.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.48 Nemadji

-
-

1.48.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.48.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.48.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.49 Oconto

-
-

1.49.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.49.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.49.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.50 Oswegatchie

-
-

1.50.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.50.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.50.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.51 PereMarquette

-
-

1.51.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.51.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.51.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
PereMarquette
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.209111
-
-
-
-

1.52 PresqueIsle

-
-

1.52.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.52.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.52.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.53 Raquette

-
-

1.53.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.53.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.53.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.54 Tahquamenon

-
-

1.54.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.54.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.54.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
-

1.55 ThunderBay

-
-

1.55.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.55.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 2 samples

-
-
-

1.55.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
ThunderBay
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.185111
-
-
-
-

1.56 WhiteMI

-
-

1.56.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 2 samples

-
-
-

1.56.2 Water Quality Guidelines, Water Samples

- - - - - - - - - - - - - - - - - - - - - - -
WhiteMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
Benzo[a]pyrenePAH0.714220.5
-
-
-

1.56.3 ToxCast, Passive

- - - - - - - - - - - - - - - - - - - - - - -
WhiteMI
ChemicalClassMaximum EARNumber of End PointsNumber of SamplesFrequency of Samples with Hits
AspirinPharmaceuticals0.25111
-
-
-
-

1.57 WhiteWI

-
-

1.57.1 ToxCast, Water Samples

-

No ToxCast, Water Sample hits in 1 samples

-
-
-

1.57.2 Water Quality Guidelines, Water Samples

-

No Water Quality Guidelines, Water Sample hits in 1 samples

-
-
-

1.57.3 ToxCast, Passive

-

No ToxCast, Passive hits in 1 sample

-
-
-
- - - - - - - - From 53ee943f231163cc7a240f0f737efb9ea4c87db6 Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Thu, 3 Nov 2016 17:43:06 -0500 Subject: [PATCH 2/8] cleanup --- vignettes/SummaryToxCast.Rmd | 975 ------------------------------ vignettes/endPointExploration.Rmd | 127 ---- vignettes/siteTables.Rmd | 188 ------ 3 files changed, 1290 deletions(-) delete mode 100644 vignettes/SummaryToxCast.Rmd delete mode 100644 vignettes/endPointExploration.Rmd delete mode 100644 vignettes/siteTables.Rmd diff --git a/vignettes/SummaryToxCast.Rmd b/vignettes/SummaryToxCast.Rmd deleted file mode 100644 index 8753786a..00000000 --- a/vignettes/SummaryToxCast.Rmd +++ /dev/null @@ -1,975 +0,0 @@ ---- -title: "Assessment of Potential Biological Effects in Great Lakes Tributaries Using ToxCast with Comparisons to Assessment Using Water Quality Guidelines." -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{ToxEval Summary} - \usepackage[utf8]{inputenc} ---- - -```{r message=FALSE, echo=FALSE} -library(grid) -library(pander) -library(dplyr) -library(tidyr) -library(DT) -library(toxEval) -library(knitr) -library(leaflet) -library(formattable) -library(ggplot2) -library(gridExtra) -library(data.table) - -pCodeInfo <- pCodeInfo -wData <- wData -endPointInfo <- endPointInfo -# AC50 data provided in the toxEval package: -AC50gain <- AC50gain -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -endPoint <- endPointToxCreate(pCodeInfo) - -# packagePath <- system.file("extdata", package="toxEval") -# filePath <- file.path(packagePath, "waterSamples.RData") -# load(file=filePath) -######################## - #Correct DEET: - # casDEET <- AC50gain$casn[AC50gain$chnm == "DEET"] - # pCodeDEET <- pCodeInfo$parameter_cd[pCodeInfo$casrn == casDEET] - # dlDEET <- min(waterSamples$valueToUse_61947, na.rm = TRUE) - # waterSamples$qualifier_61947 <- ifelse(waterSamples$valueToUse_61947 <= dlDEET*4, "<", "") -######################## -# Just removing DEET: -# waterSamples <- waterSamples[,-grep("61947",x = names(waterSamples))] -# pCodeInfo <- pCodeInfo[pCodeInfo$parameter_cd != "61947",] -# waterSamples$site["USGS-04157005" == waterSamples$site] <- "USGS-04157000" -# -# waterSamplePCodes <- names(waterSamples)[grep("valueToUse", -# names(waterSamples))] -# waterSamplePCodes <- sapply(strsplit(waterSamplePCodes, "_"), function(x) x[2]) -# -# qualColumns <- grep("qualifier", names(waterSamples)) -# valColumns <- grep("valueToUse", names(waterSamples)) -# -# waterData <- waterSamples[,valColumns] -# waterData[waterSamples[,qualColumns] == "<"] <- 0 -# -# wData <- cbind(waterSamples[,1:2],waterData) -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -chemSum2 <- chemSumm(chemicalSummary) - -summary <- siteSumm(chemicalSummary,newSiteKey) - -``` - - -```{r, echo=FALSE} - -packagePath <- system.file("extdata", package="toxEval") -# filePath <- file.path(packagePath, "passiveData.RData") -# load(file=filePath) - -passiveData <- passiveData - -#passive class info: -passiveCAS <- readRDS(file.path(packagePath, "passiveCAS.rds")) - -# pCodeInfo <- pCodeInfo[pCodeInfo$casrn != "", ] - -# # Some chemicals have 2 rows (different units)... -# # To simplify for now, we'll ignore the duplicate chemicals: -# -# -# passiveData <- left_join(passiveData, passiveCAS, by=c("CAS", "Chemical")) -# passiveData <- passiveData[!duplicated(passiveData$CAS),] -# passiveData$class[passiveData$Chemical == "Hexachlorobenzene (HCB)"] <-"OC Pesticides" -# passiveData$class[passiveData$Chemical == "Pentachloroanisole (PCA)"] <-"OC Pesticides" -# passiveData$class[is.na(passiveData$class)] <-"Pharmaceuticals" -# -# passiveData <- passiveData[,-which(names(passiveData) == "site04249000.1")] - - -unitConversion <- setNames(c(10^6, 10^3), c("pg/L", "ng/L") ) - -AC50_passive <- right_join(AC50gain[,c("casn"), drop=FALSE], - passiveData[,c("CAS", "Units", "mlWt","Chemical")], - by= c("casn" = "CAS")) %>% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) - -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) %>% - mutate(hits = as.numeric(EAR > 0.1), - endPoint=as.character(endPoint)) %>% - filter(!is.na(EAR)) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemSum2_passive <- chemSumm(chemicalSummary_passive) - -summ1_passive <- siteSumm(chemicalSummary_passive, newSiteKey) - -``` - - -```{r, eval=TRUE, echo=FALSE} - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) -chemSum2_BM <- chemSumm(chemicalSummary_BM) - - -summary_BM <- siteSumm(chemicalSummary_BM,newSiteKey) - - - -``` - -# Introduction {#intro} - -## Screening Endpoints Used in Analysis - -* ToxCast: (EPA NCCT) - * "High throughput screening assays" - * In-vitro Exposures to living cells or isolated proteins - * Screens for potential adverse biological effects - * Much is focused on gaining information on biological pathways - * 1860 compounds - * 821 endpoints - * AC50 used for this analysis (concentration at which activity is 50% of its maximum) - * Exposure:Activity Ratio (EAR) = concentration / AC50 -* Established Water quality guidelines - * Water sample analysis (not complete for passive samplers yet) - * USEPA - * Canadian Council of Ministers of the Environment - * USGS - * Literature - -## Matches of Screening Endpoints -* Which chemicals are included in ToxCast and Water Quality Guideline assessments? - + Water samples - * `r length(unique(chemSum2$chnm))` compounds of `r nrow(pCodeInfo)` total - * `r paste(unique(chemSum2$class), collapse=", ")` - + Passive samplers - * `r length(unique(chemSum2_passive$chnm))` compounds of `r length(unique(passiveData$Chemical))` total - * `r paste(unique(chemSum2_passive$class), collapse=", ")` -* Water Quality Guidelines - + Water samples - * `r length(unique(chemSum2_BM$chnm))` compounds of `r nrow(pCodeInfo)` total - * `r paste(unique(chemSum2_BM$class), collapse=", ")` - - -# ToxCast, Water Sample Data {#toxWS} - -Water samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis. - -```{r echo=FALSE, eval=TRUE} -library(knitr) -library(pander) -ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)",rep("", 8)) - -df <- data.frame(ws=ws, stringsAsFactors=FALSE) - -names(df) <- c("Water Samples: Organic Waste Compounds") - -pander(df) - -``` - - -## ToxCast, Water Samples: Detection Levels - -As an initial exploration of limitations of using ToxCast with the water sample data, ToxCast endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level for the endpoint with the minimum AC50 for that chemical is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "waterSamples.RData") -load(file=filePath) - -waterSamples$site["USGS-04157005" == waterSamples$site] <- "USGS-04157000" - - -pCodeSummary <- select(pCodeInfo, srsname, casrn, parameter_units, mlWt) - -detectionLimits <- waterSamples[,grep("detectionLimit", names(waterSamples))] -detectionLimits <- na.omit(detectionLimits) - -detLevels <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue,-class, -minDetLevel,-chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## ToxCast, Water Samples: Chemical Summary Tables - -This table focuses on the individual compounds and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} - -datatable(chemSum2[,-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) -``` - -### ToxCast, Water Samples: Individual EndPoints -This table focuses on the individual endpoint/compound combinations and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r message=FALSE, results='asis', echo=FALSE} - - -chemSum3 <- chemicalSummary %>% - group_by(chnm, class, site, endPoint) %>% - summarize(hits=as.numeric(any(hits > 0)), - maxEAR=max(EAR)) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits), - maxEAR=max(maxEAR)) %>% - rename(assay_component_endpoint_name=endPoint) %>% - data.table() %>% - left_join(data.table(endPointInfo), by="assay_component_endpoint_name") %>% - select(chnm, maxEAR, freq, nSites, - endPoint=assay_component_endpoint_name, class, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(chemSum3[,-4]), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -endpointSummary <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -endpointSummary <- endpointSummary %>% - select(endPoint, maxEAR, freq, nSites, - endPoint, contains("intended_target_")) %>% - rename(type=intended_target_type, type_sub=intended_target_type_sub, - family=intended_target_family, family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) - - datatable(distinct(endpointSummary), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("End Point","Maximum EAR","Fraction of Sites with Hits","nSites","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - - -``` - -## ToxCast, Water Samples: Site Summaries - -This table focuses on the individual sites and the prevalence of potential adverse biological effects (`r length(unique(chemSum2$chnm))` total chemicals included in ToxCast). The table can be sorted by the fraction of samples with hits, number of chemicals with hits, number of endpoints with hits, maximum EAR, and land cover attributes to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -summary_display <- left_join(summary, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display, rownames = FALSE, - colnames=c("Station Name","Fraction of Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) -``` - -## ToxCast, Water Sample: Boxplots by Site -This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits, number of chemicals with hits, and the total number of collected samples is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -siteLimits <- filter(summary_display, freq>0) %>% - arrange(desc(nChem), desc(nEndPoints)) %>% - select(site,nEndPoints,nChem, nSamples) - - -summary_display2 <- chemicalSummary %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sToxWS <- ggplot(summary_display2, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$site) + - scale_y_log10(limits=c(0.03,5000)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.07, - label=siteLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.045, - label=siteLimits$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits$site, y=0.03, - label=siteLimits$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - - -g_sToxWS <- ggplotGrob(sToxWS) -g_sToxWS$layout$clip[g_sToxWS$layout$name=="panel"] <- "off" -grid.draw(g_sToxWS) - -``` - -## ToxCast, Water Sample: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits <- filter(chemSum2, freq>0) %>% - arrange(desc(freq),desc(nEndPoints)) %>% - select(chnm, nEndPoints, freq) %>% - mutate(freq=sprintf("%.0f",100*freq)) - -chemicalSummary_display <- chemicalSummary %>% - filter(EAR>=0.1) - -chemToxWS <- ggplot(chemicalSummary_display, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits$chnm) + - scale_y_log10(limits=c(0.045,5000)) + - labs(x = "Chemical Name")+ - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.07, - label=chemLimits$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits$chnm, y=0.045, - label=chemLimits$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.8, xmax = -0.8, ymin = log10(0.045), ymax = log10(0.045)) - -g_chemToxWS <- ggplotGrob(chemToxWS) -g_chemToxWS$layout$clip[g_chemToxWS$layout$name=="panel"] <- "off" -grid.draw(g_chemToxWS) - -``` - -# ToxCast, Passive Data {#toxPassive} - -Passive samples were analyzed for the following classes of compounds with the number of individual compounds per class in parenthesis. - -```{r echo=FALSE, eval=TRUE} -library(knitr) -library(pander) -# ws <- c("PAH (6)", "Insecticides (6)", "Herbicides (7)", "Fire retardants (4)", "Pharmaceuticals (3)", "Plasticizers (5)", "Detergent metabolites (8)", "Antimicrobial disinfectants (3)", "Solvents (2)", "Fuels (4)", "Dye/pigments (1)", "Flavors & fragrances (10)", "Sterols (4)", "Misc (3)") - -ps <- c("PAH (33)", "Organic Waste Compounds (53)", "Organochlorine Pesticides (32)", "PBDEs (5)", "Pharmaceuticals (31)", "PCB (sum of total)") - -df <- data.frame(ps=ps, stringsAsFactors=FALSE) - -names(df) <- c("Passive Samples") - -pander(df) - -``` - - -## ToxCast, Passive: Detection Levels - -As an initial exploration of limitations of using ToxCast with the passive data, ToxCast endpoints were compared with detection levels (MQL) for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} - -detLevels_passive <- select(passiveData, Chemical, MQL, CAS, class) %>% - right_join(endPoint_passive, by=c("CAS"="casn")) %>% - select(-mlWt, -conversion, -Chemical, -CAS) %>% - gather(endPoint,endPointValue,-MQL,-chnm, -Units,-class) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=MQL/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel=MQL) %>% - arrange(desc(EAR)) - - -datatable(detLevels_passive, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## ToxCast, Passive: Chemical Summary Tables - -This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), and number of endpoints with hits to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -chemSum2_passive_dt <- chemSum2_passive[,-6:-7] %>% - filter(freq > 0) - -datatable(chemSum2_passive_dt, rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits")) %>% - formatRound(c("maxEAR", "freq"), digits = 4) - -``` - -### ToxCast, Passive: Individual EndPoints -This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum exposure:activity ratio (EAR), endpoints with hits, and several variables that describe the ToxCast endpoints to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r message=FALSE, results='asis', echo=FALSE} - - -chemSum3_passive <- chemicalSummary_passive %>% -# group_by(chnm, class, site, endPoint) %>% -# summarize(hits= as.numeric(any(EAR > 0.1))) %>% - group_by(chnm, class, endPoint) %>% - summarize(freq=sum(hits)/n_distinct(site), - nSites=sum(hits)) - -chemSum4_passive <- chemicalSummary_passive %>% - group_by(chnm, class, endPoint) %>% - summarize(maxEAR=max(EAR), - nSamples=1) %>% - left_join(chemSum3_passive, by=c("chnm","class","endPoint")) %>% - select(chnm, class, freq, maxEAR, nSamples, endPoint) %>% - left_join(endPointInfo, by=c("endPoint"="assay_component_endpoint_name")) %>% - select(chnm, maxEAR, freq, endPoint, class, contains("intended_target_")) %>% - rename(type=intended_target_type, - type_sub=intended_target_type_sub, - family=intended_target_family, - family_sub=intended_target_family_sub) %>% - select(-contains("intended_target_")) %>% - data.frame %>% - arrange(desc(freq)) %>% - filter(freq > 0) - - - datatable(distinct(chemSum4_passive), rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Maximum EAR","Fraction of Sites with Hits","Endpoint","Class","Type","Type_sub","Family","Family_sub")) %>% - formatRound(c("maxEAR", "freq"), digits = 2) - -``` - -## ToxCast, Passive: Site Summaries - -This table focuses on the individual sites, and the prevalence of potential adverse biological effects (`r length(unique(chemSum2_passive$chnm))` total chemicals included in ToxCast). The table can be sorted by number of chemicals with hits, number of endpoints with hits, maximum exposure:activity ratio (EAR), and land cover attributes to evaluate results based on different priorities. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - -```{r, echo=FALSE, results='asis'} -summary_display_passive <- left_join(summ1_passive, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -summary_display_passive <- summary_display_passive[,c(-2,-3)] -datatable(summary_display_passive, rownames = FALSE, - colnames=c("Station Name", "Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR", "Ag [%]", "Urban [%]")) %>% -# options = list(pageLength = 50)) %>% - formatRound(c("maxEAR"), digits = 2) -``` - -## ToxCast, Passive: Boxplots by Sites - -This figure displays ranges of exposure:activity ratio (EAR) values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -summary_display1_passive <- transform(summary_display_passive, - site = reorder(site, order(nChem,decreasing=TRUE))) - -siteLimits_passive <- filter(summary_display_passive, nChem>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem) - -summary_display2_passive <- chemicalSummary_passive %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - -sp <- ggplot(summary_display2_passive, aes(x=site, y=EAR)) + - geom_point() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - ylim(-1,10) + - scale_x_discrete(limits=siteLimits_passive$site)+ - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-0.5, label=siteLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_passive$site, - y=-1, label=siteLimits_passive$nChem),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.7, xmax = -0.7, ymin = -1, ymax = -1) - -g_sp <- ggplotGrob(sp) -g_sp$layout$clip[g_sp$layout$name=="panel"] <- "off" -grid.draw(g_sp) - - -``` - - -## ToxCast, Passive: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits_passive <- filter(chemSum2_passive, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq=sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, nSites) - -chemicalSummary_display_passive <- chemicalSummary_passive %>% - filter(EAR>=0.1) - -cp <- ggplot(chemicalSummary_display_passive, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - ylim(-1,10) + - scale_x_discrete(limits=chemLimits_passive$chnm) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-0.5, - label=chemLimits_passive$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_passive$chnm, y=-1, - label=chemLimits_passive$nSites),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -0.5, ymax = -0.5) + - annotation_custom(grob=textGrob("Sites:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = 0.5, xmax = 0.5, ymin = -1, ymax = -1) - - -g_cp <- ggplotGrob(cp) -g_cp$layout$clip[g_cp$layout$name=="panel"] <- "off" -grid.draw(g_cp) - -``` - - -# Water Quality Guidelines, Water Samples {#WQGws} - -## Water Quality Guidelines, Water Samples: Detection Levels - -As an initial exploration of limitations of using water quality guidelines with the water sample data, water quality guidelines endpoints were compared with detection levels for each analyzed compound. The exposure:activity ratio (EAR) for a concentration at the detection level is presented in this table. Only compounds with detection levels great than 10% of the lowest AC50 are included. - -```{r warning=FALSE, echo=FALSE} - -detLevels_BM <- data.frame(dl_pcode=names(detectionLimits), - minDetLevel=apply(detectionLimits, 2, min), - row.names=NULL, stringsAsFactors=FALSE) %>% - mutate(pCode=sapply(strsplit(dl_pcode, "_"), function(x) x[2])) %>% - left_join(pCodeInfo[c("parameter_cd","casrn","class")], - by=c("pCode"="parameter_cd")) %>% - select(casrn, class, minDetLevel) %>% - right_join(endPoint_bm, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn) %>% - gather(endPoint,endPointValue,-class, -minDetLevel,-chnm,-Units) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=minDetLevel/endPointValue) %>% - filter(EAR >= 0.1) %>% - select(Chemical=chnm, Class=class, EAR, endPoint, minDetLevel) %>% - arrange(desc(EAR)) - - -datatable(detLevels_BM, rownames = FALSE,options = list(pageLength = 10)) %>% - formatRound(c("EAR","minDetLevel"), digits = 1) - -``` - - -## Water Quality Guidelines, Water Samples: Chemical Summary Tables - -This table focuses on the individual compounds, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, and number of endpoints with hits to evaluate results based on different priorities."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - - -```{r, echo=FALSE, results='asis'} - -datatable(chemSum2_BM[-6], rownames = FALSE, - options = list(pageLength = 10), - colnames=c("Chemical","Class","Fraction of Sites with Hits","Maximum EAR","Number of End Points with Hits", "Total Samples")) %>% - formatRound(c("maxEAR", "freq"), digits = 3) -``` - -## Water Quality Guidelines, Water Samples: Site Summaries - -This table focuses on the individual endpoint/compound combinations, and the prevalence of potential adverse biological effects (57 total sites). The table can be sorted by the fraction of sites with hits, maximum EAR, endpoints with hits, and several variables that describe the water quality benchmark endpoints to evaluate results based on different priorities."Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. - - -```{r, echo=FALSE, results='asis'} -summary_display_BM <- left_join(summary_BM, stationINFO[,c("shortName","Ag.pct","Urban.pct")], by=c("site"="shortName")) - -datatable(summary_display_BM, rownames = FALSE, - colnames=c("Station Name","Fraction Samples with Hits", "Total Samples","Number of Chemicals with Hits", "Number of End Points with Hits", "Maximum EAR","Ag [%]","Urban [%]")) %>% - formatRound(c("freq","maxEAR","Ag.pct","Urban.pct"), digits = 2) -``` - - -## Water Quality Guidelines, Water Samples: Boxplots by Site - -This figure displays ranges of EAR values for each site. Information on the number of endpoints with hits and number of chemicals with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -siteLimits_BM <- filter(summary_display_BM, freq>0) %>% - arrange(desc(nChem)) %>% - select(site,nEndPoints,nChem,nSamples) - -summary_display2_BM <- chemicalSummary_BM %>% - mutate(site=as.character(newSiteKey[site])) %>% - select(site, chnm, EAR, endPoint, class, date) %>% - arrange(site, chnm, EAR)%>% - filter(EAR>0.1) - - -sBenchWS <- ggplot(summary_display2_BM, aes(x=site, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits_BM$site) + - scale_y_log10(limits=c(0.03,250)) + - labs(x = "Site") + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.07, - label=siteLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.045, - label=siteLimits_BM$nChem),size=3) + - geom_text(data=data.frame(), aes(x=siteLimits_BM$site, y=0.03, - label=siteLimits_BM$nSamples),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Chemicals:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.045), ymax = log10(0.045)) + - annotation_custom(grob=textGrob("Samples:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.9, xmax = -0.9, ymin = log10(0.03), ymax = log10(0.03)) - -g_sBenchWS <- ggplotGrob(sBenchWS) -g_sBenchWS$layout$clip[g_sBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_sBenchWS) - - -``` - -## Water Quality Guidelines, Water Samples: Boxplots by Chemical - -This figure displays ranges of EAR values for each chemical. Information on the number of endpoints with hits, and percentage of sites with hits is included. "Hits" are defined as EAR > 0.1, indicating that the measured concentration is 10% of the AC50 or greater. Only samples with hits are included. - -```{r fig.width=7, fig.height=7, echo=FALSE,warning=FALSE, message=FALSE} - -chemLimits_BM <- filter(chemSum2_BM, freq>0) %>% - arrange(desc(freq)) %>% - mutate(freq = sprintf("%.0f",100*freq)) %>% - select(chnm, nEndPoints, freq) - -chemicalSummary_display_BM <- chemicalSummary_BM %>% - filter(EAR>=0.1) - -cBenchWS <- ggplot(chemicalSummary_display_BM, aes(x=chnm, y=EAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25), - legend.position = "none") + - scale_x_discrete(limits=chemLimits_BM$chnm) + - scale_y_log10(limits=c(0.045,250)) + - labs(x = "Chemical Name") + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.07, - label=chemLimits_BM$nEndPoints),size=3) + - geom_text(data=data.frame(), aes(x=chemLimits_BM$chnm, y=0.045, - label=chemLimits_BM$freq),size=3) + - annotation_custom(grob=textGrob("EndPoints:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.07), ymax = log10(0.07)) + - annotation_custom(grob=textGrob("Site Hits [%]:", gp = gpar(fontface = "italic", fontsize = 8)),xmin = -0.2, xmax = -0.2, ymin = log10(0.045), ymax = log10(0.045)) - -g_cBenchWS <- ggplotGrob(cBenchWS) -g_cBenchWS$layout$clip[g_cBenchWS$layout$name=="panel"] <- "off" -grid.draw(g_cBenchWS) -``` - - -# Comparisons - -This table is a comparison of the three different bio-effect evaluations (ToxCast with water samples, ToxCast with passive samples, water quality guidelines with water samples). The three classes that most commonly have potential adverse effects are highlighted (PAHs, pharmaceuticals, and pesticides). - -```{r echo=FALSE} -# ToxCast Water Samples: -toxWS <- chemSum2 %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm,class,freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive <- chemSum2_passive %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -toxPassive$Class[toxPassive$Class == "PAHs"] <- "PAH" - -tradWS <- chemSum2_BM %>% - filter(freq>0)%>% - arrange(desc(freq)) %>% - select(chnm, class, freq) %>% - rename(Chemical=chnm, Class=class) - -tradWS <- tradWS[1:20,1:2] -toxPassive <- toxPassive[1:20,1:2] -toxWS <- toxWS[1:20,1:2] - -combo <- cbind(toxWS, toxPassive, tradWS) -names(combo) <- c("ToxCast-Water Samples: Chemical", "ToxCast-Water Samples: Class","ToxCast-Passive: Chemical", "ToxCast-Passive: Class","WQG-Water Samples: Chemical", "WQG-Water Samples: Class") -# emphasize.strong.cells(which(combo == "PAH", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, style = 'simple', split.table = Inf) - - -``` - - -```{r, echo=FALSE, results='asis'} -formattable(combo, list( - 'ToxCast-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'ToxCast-Passive: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))), - 'WQG-Water Samples: Class' = formatter("span", - style = x ~ ifelse(x == "PAH", - style(color = "green", font.weight = "bold"), - ifelse( x == "Pharmaceuticals", - style(color = "red", font.weight = "bold"), - ifelse(x == "Herbicide" | x == "Insecticide", - style(color = "blue", font.weight = "bold"),NA)))) -)) - -# emphasize.strong.cells(which(combo == "Herbicide" | combo == "Insecticide", arr.ind = TRUE)) -# pander(combo,row.names = FALSE, split.table = Inf) -``` - - -# Maps {#maps} - -## ToxCast, Water Samples: Map -This map summarizes the water sample ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-19) - -```{r, echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5} -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapData <- left_join(stationINFO, summary, by=c("shortName"="site")) -mapData <- mapData[!is.na(mapData$dec.lat.va),] -mapData <- mapData[!is.na(mapData$nChem),] - - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,5,10,100,1000,2500)#seq(0,2500, 500) # This is maxEAR - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(5000,15000, 500) -mapData$sizes <- rad[as.numeric(cut(mapData$nChem, c(-1:19)))] - -pal = colorBin(col_types, mapData$maxEAR, bins = leg_vals) - -m = leaflet(mapData) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0('',mapData$Station.Name,"
", - "', - "', - "', - "', - "
Frequency",sprintf("%1.1f",mapData$freq),'
nSample",mapData$nSamples,'
maxEAR",sprintf("%1.1f",mapData$maxEAR),'
nChem",mapData$nChem,'
nEndPoints",mapData$nEndPoints,'
') - , - fillColor = ~pal(maxEAR), - weight = 1, - color = "black", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, - opacity = 0.8, - title = 'Maximum EAR') - -m - -``` - -## ToxCast, Passive: Map -This map summarizes the passive ToxCast results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-3) - -```{r, echo=FALSE, results='asis', echo=FALSE, fig.width=7, fig.height=5} - -stationINFO <- stationINFO[!is.na(stationINFO$dec.lat.va),] - -mapDataPassive <- left_join(stationINFO, summ1_passive, by=c("shortName"="site")) -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$dec.lat.va),] -mapDataPassive <- mapDataPassive[!is.na(mapDataPassive$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals <- c(0,1,2,3,5,7,9)#seq(0,2500, 500) # This is maxEAR scale - -cols <- colorNumeric(col_types, domain = leg_vals) -rad <- seq(2500,15000, 2500) -mapDataPassive$sizes <- rad[as.numeric(cut(mapDataPassive$nChem, c(-1,0,1,2,3)))] -mapDataPassive$sizes[is.na(mapDataPassive$sizes)] <- 1000 - -pal = colorBin(col_types, mapDataPassive$maxEAR, bins = leg_vals) - - -map2 = leaflet(mapDataPassive) %>% -# addProviderTiles("Hydda.Full") %>% # There are more maybe worth looking at - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup= - paste0("",mapDataPassive$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f",mapDataPassive$maxEAR),'
nChem",mapDataPassive$nChem,'
nEndPoints",mapDataPassive$nEndPoints,'
'), - fillColor = ~pal(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map2 - -``` - - -## Water Quality Guidelines, Water Samples: Map -This map summarizes the passive water quality guideline results by showing maximum exposure:activity ratio (EAR) for each site as the color scale, and number of chemicals with hits as the symbol size. Additional information is available by clicking on the points. - -Color: Maximum EAR
-Size: Number of chemicals with hits (0-10) - -```{r echo=FALSE, results='asis', fig.width=7, fig.height=5} -mapDataWQ <- left_join(stationINFO, summary_BM, by=c("shortName"="site")) -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$dec.lat.va),] -mapDataWQ <- mapDataWQ[!is.na(mapDataWQ$maxEAR),] - -col_types <- c("darkblue","dodgerblue","green","yellow","orange","red") -leg_vals_BM <- c(0,1,25,50,75,100,125)#seq(0,2500, 500) # This is maxEAR scale - -colsWQ <- colorNumeric(col_types, domain = leg_vals_BM) -radWQ <- seq(2500,15000, 2500) -mapDataWQ$sizes <- rad[as.numeric(cut(mapDataWQ$nChem, c(-1,0,1,5,10)))] -mapDataWQ$sizes[is.na(mapDataWQ$sizes)] <- 1000 - -palWQ = colorBin(col_types, mapDataWQ$maxEAR, bins = leg_vals_BM) - - -map4 = leaflet(mapDataWQ) %>% - addProviderTiles("Esri.WorldPhysical") %>% - setView(lng = -83.5, lat = 44.5, zoom=6)%>% - addCircles(lat=~dec.lat.va, lng=~dec.long.va, - popup=paste0("",mapDataWQ$Station.Name,"
", - "', - "', - "
maxEAR",sprintf("%1.1f", mapDataWQ$maxEAR),'
nChem",mapDataWQ$nChem,'
nEndPoints", mapDataWQ$nEndPoints,'
'), - fillColor = ~palWQ(maxEAR), - weight = 1, - color = "blue", - fillOpacity = 0.8, radius = ~sizes, opacity = 0.8) %>% - addLegend( - position = 'bottomleft', - pal=pal, - values=~maxEAR, -# colors = cols(leg_vals), - opacity = 0.8, -# labels = paste0(leg_vals,'-'), - title = 'Maximum EAR') -map4 - -``` - - - - - diff --git a/vignettes/endPointExploration.Rmd b/vignettes/endPointExploration.Rmd deleted file mode 100644 index 83d73433..00000000 --- a/vignettes/endPointExploration.Rmd +++ /dev/null @@ -1,127 +0,0 @@ ---- -title: "EndpointExploration" -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{ToxEval Summary} - \usepackage[utf8]{inputenc} ---- - -```{r message=FALSE, echo=TRUE, results='asis'} -library(toxEval) -library(DT) -library(dplyr) -library(tidyr) - -wData <- wData -pCodeInfo <- pCodeInfo - -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) - -endPoint <- endPointToxCreate(pCodeInfo) -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -endPointInfo <- endPointInfo -# epSumm <- endPointSumm(chemicalSummary, endPointInfo=endPointInfo) - -siteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) -summary <- siteSumm(chemicalSummary,siteKey) - -``` - - -```{r } -group <- "transcription factor" -groupCol <- "intended_target_type_sub" -chemicalSummary.site <- "site" -chemicalSummary.Key <- "endPoint" -chemicalSummary.Date <- "date" -funcToSummerise <- "sumEAR" - -endPointInfoSub <- select_(endPointInfo, "assay_component_endpoint_name", groupCol) %>% - unique() - -chemicalSummary <- chemicalSummary %>% - filter(endPoint %in% endPointInfoSub$assay_component_endpoint_name ) %>% - left_join(endPointInfoSub, - by=c("endPoint"="assay_component_endpoint_name")) - -groupSumm <- chemicalSummary %>% - group_by(site) %>% - summarise(nChem = length(unique(chnm)), - nEndPoints = length(unique(endPoint))) %>% - select(nChem,nEndPoints) %>% - mutate(nChem = median(nChem), - nEndPoints = median(nEndPoints)) %>% - unique() - -endpointSummary <- chemicalSummary %>% - filter_(paste0(groupCol," == '", group, "'")) %>% - select_("hits","EAR","endPoint", - chemicalSummary.site,chemicalSummary.Date,groupCol) %>% - group_by_(chemicalSummary.site, chemicalSummary.Date) %>% - summarise(sumEAR = sum(EAR), - nHits = sum(hits)) - -statsOfSum <- endpointSummary%>% - group_by_(chemicalSummary.site) %>% - summarise_(meanEAR = paste0("mean(",funcToSummerise,")"), - # medianEAR = paste0("median(",funcToSummerise,")"), - maxEAR = paste0("max(",funcToSummerise,")"), - sumHits = "sum(nHits)", - nSamples = "n()")%>% - data.frame()%>% - mutate(site = siteKey[site]) - - - - - -datatable(statsOfSum, rownames = FALSE, - caption=paste("Summary of", funcToSummerise, "of",group)) %>% - formatRound(c("meanEAR","maxEAR","sumHits","nSamples"), - digits = 1) - - -``` - - -```{r fig.width=7, fig.height=7,} -library(ggplot2) - -siteLimits <- stationINFO %>% - mutate(lakeCat = factor(Lake, - levels=c("Lake Superior","Lake Michigan", - "Lake Huron", "St. Lawrence River", - "Detroit River and Lake St. Clair","Lake Erie","Lake Ontario"))) %>% - arrange(lakeCat) %>% - mutate(lakeColor = c("red","black","green","brown","brown","brown","blue")[as.numeric(lakeCat)] ) %>% - filter(fullSiteID %in% unique(endpointSummary$site)) - - -endPointSummBP <- endpointSummary %>% - data.frame()%>% - mutate(site = siteKey[site]) %>% - mutate(site = factor(site, levels=siteLimits$Station.shortname)) - -sToxWS <- ggplot(endPointSummBP, aes(x=site, y=sumEAR)) + - geom_boxplot() + - theme(axis.text.x = element_text(angle = 90, hjust = 1,vjust=0.25, colour=siteLimits$lakeColor), - legend.position = "none")+ - scale_x_discrete(limits=siteLimits$Station.shortname) + - # scale_y_log10(limits=c(0.03,5000)) + - # labs(x = "Site") + - geom_text(data=data.frame(), aes(x=c(5, 18,31,45,56), - y=-.5, label=c("Superior","Michigan","Huron","Erie","Ontario")), - colour=factor(c("red","black","green","brown","blue"), - levels=c("red","black","green","brown","blue")), size=3) - -sToxWS -``` diff --git a/vignettes/siteTables.Rmd b/vignettes/siteTables.Rmd deleted file mode 100644 index 97ae571d..00000000 --- a/vignettes/siteTables.Rmd +++ /dev/null @@ -1,188 +0,0 @@ ---- -title: "Site Tables" -author: "USGS: Steve Corsi, Laura DeCicco, Austin Baldwin, David Alvarez, Peter Lenaker
USEPA: Anthony Schroeder, Dan Villeneuve, Brett Blackwell, Gerald Ankley" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: - rmarkdown::html_vignette: - toc: true - number_sections: true - fig_caption: yes - toc_depth: 2 -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteIndexEntry{Site Tables} - \usepackage[utf8]{inputenc} ---- - -# Site Tables - -```{r message=FALSE, echo=FALSE, results='asis',warning=FALSE} -library(dplyr) -library(tidyr) -library(DT) -library(toxEval) -library(knitr) - - -pCodeInfo <- pCodeInfo -wData <- wData -endPointInfo <- endPointInfo -# AC50 data provided in the toxEval package: -AC50gain <- AC50gain -packagePath <- system.file("extdata", package="toxEval") -filePath <- file.path(packagePath, "stationINFO.RData") -load(file=filePath) -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -endPoint <- endPointToxCreate(pCodeInfo) - -AC50gain_bm <- select(pCodeInfo, srsname, casrn, AqT_EPA_acute, - AqT_EPA_chronic, AqT_other_acute, AqT_other_chronic) - -AC50_bm <- left_join(AC50gain_bm, pCodeInfo[,c("casrn", "parameter_units", "mlWt")], by= c("casrn"="casrn")) %>% - filter(!is.na(parameter_units)) %>% - rename(desiredUnits = parameter_units) %>% - mutate(conversion = 1) %>% - select(casrn, srsname, desiredUnits, mlWt, conversion) - -AC50Converted_bm <- left_join(AC50_bm, AC50gain_bm, by = c("casrn", "srsname")) %>% - rename(casn=casrn, chnm=srsname) - -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion") - -endPointData_bm <- AC50Converted_bm[,!(names(AC50Converted_bm) %in% infoColumns)] -endPointData_bm <- endPointData_bm * AC50Converted_bm$conversion -AC50_bm <- rename(AC50_bm, casn=casrn, chnm=srsname) -endPoint_bm <- cbind(AC50_bm, data.frame(endPointData_bm)) -endPoint_bm <- rename(endPoint_bm, Units=desiredUnits) - -unitConversion <- setNames(c(10^6, 10^3), c("pg/L", "ng/L") ) - -AC50_passive <- right_join(AC50gain[,c("casn"), drop=FALSE], - passiveData[,c("CAS", "Units", "mlWt","Chemical")], - by= c("casn" = "CAS")) %>% - rename(desiredUnits = Units, chnm=Chemical) %>% - filter(!is.na(mlWt)) %>% - mutate(conversion = unitConversion[desiredUnits] * mlWt) %>% - select(casn, chnm, desiredUnits, mlWt, conversion) - -AC50Converted_passive <- left_join(AC50_passive, AC50gain, by = c("casn", "chnm")) -infoColumns <- c("casn", "chnm", "desiredUnits","mlWt", "conversion", "code","chid") - -endPointData_passive <- AC50Converted_passive[,!(names(AC50Converted_passive) %in% infoColumns)] -endPointData_passive <- 10^endPointData_passive -endPointData_passive <- endPointData_passive * AC50Converted_passive$conversion -endPoint_passive <- cbind(AC50_passive, data.frame(endPointData_passive)) -endPoint_passive <- rename(endPoint_passive, Units=desiredUnits) - -siteColumns <- grep("site",names(passiveData)) -passiveData[,siteColumns] <- suppressWarnings( - sapply(passiveData[,siteColumns], function(x) as.numeric(x))) -#For this analysis, we'll consider NA's to be 0 (other options exist): -passiveData[,siteColumns][is.na(passiveData[,siteColumns])] <- 0 - -newSiteKey <- setNames(stationINFO$shortName, stationINFO$fullSiteID) - -infoColumns <- c("Chemical", "CAS", "Units", "MLD", "MQL", "mlWt","class") - -chemicalSummary_passive <- passiveData %>% - gather(site, measuredValue, which(!(names(passiveData) %in% infoColumns) )) %>% - filter(!is.na(measuredValue)) %>% - select(casrn=CAS,class, measuredValue, site)%>% - right_join(endPoint_passive, by=c("casrn"="casn")) %>% - select(-mlWt, -conversion, -casrn, -Units) %>% - gather(endPoint, endPointValue, -class, -site, -measuredValue, -chnm) %>% - filter(!is.na(endPointValue)) %>% - mutate(EAR=measuredValue/endPointValue) - -chemicalSummary_passive <- chemicalSummary_passive %>% - mutate(site=paste0("USGS-",gsub("[^0-9]", "", as.character(site))))%>% - mutate(date=as.POSIXct(NA)) - -chemicalSummary <- chemSummBasic(wData,pCodeInfo,endPoint) -chemicalSummary_BM <- chemSummBasic(wData,pCodeInfo,endPoint_bm) - -siteSummary <- siteSumm(chemicalSummary,newSiteKey) - -for(i in siteSummary$site){ - - chemSummSite <- filter(chemicalSummary, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_BM <- filter(chemicalSummary_BM, site == names(newSiteKey)[i == newSiteKey]) - chemSummSite_passive <- filter(chemicalSummary_passive, site == names(newSiteKey)[i == newSiteKey]) - - totalSamples <- select(chemSummSite,date,site) %>% - distinct()%>% - nrow() - - - chemSummSite2 <- select(chemSummSite,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_BM <- select(chemSummSite_BM,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite2_passive <- select(chemSummSite_passive,-site, -endPoint, -endPointValue) %>% - mutate(hits=as.numeric(EAR > 0.1))%>% - group_by(chnm,class,date)%>% - summarize(hits=as.numeric(any(hits>0)))%>% - group_by(chnm,class)%>% - summarize(freq=sum(hits)/n_distinct(date)) - - chemSummSite1 <- chemSumm(chemSummSite) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_BM <- chemSumm(chemSummSite_BM) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_BM, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - chemSummSite1_passive <- chemSumm(chemSummSite_passive) %>% - select(-nSites,-freq)%>% - left_join(chemSummSite2_passive, by=c("chnm","class"))%>% - data.frame()%>% - filter(maxEAR > 0.1) %>% - arrange(desc(maxEAR)) - - names(chemSummSite1) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_BM) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - names(chemSummSite1_passive) <- c("Chemical", "Class","Maximum EAR", "Number of End Points", "Number of Samples","Frequency of Samples with Hits") - - cat("\n\n##", i, "\n") - cat("\n###ToxCast, Water Samples\n") - - if(nrow(chemSummSite1) > 0){ - print(kable(chemSummSite1, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###Water Quality Guidelines, Water Samples\n") - if(nrow(chemSummSite1_BM) > 0){ - print(kable(chemSummSite1_BM, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo Water Quality Guidelines, Water Sample hits in ",totalSamples," samples\n") - } - cat("\n###ToxCast, Passive\n") - if(nrow(chemSummSite1_passive) > 0){ - print(kable(chemSummSite1_passive, digits=3,caption = i, row.names = FALSE)) - } else { - cat("\nNo ToxCast, Passive hits in 1 sample\n") - } -} - -``` \ No newline at end of file From 509a8d07020c0763df0f92c758b776a6357112ef Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Thu, 3 Nov 2016 17:43:38 -0500 Subject: [PATCH 3/8] moving around data --- NAMESPACE | 1 + 1 file changed, 1 insertion(+) diff --git a/NAMESPACE b/NAMESPACE index 87f768f2..48390af3 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -10,6 +10,7 @@ export(endPointSumm) export(endPointToxCreate) export(explore_endpoints) export(flagDF) +export(pCodeInfo) export(siteSumm) export(totalSamples) import(DT) From 588796ef971a0da1604ded6ca36609ce0ee330f2 Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Thu, 3 Nov 2016 17:44:37 -0500 Subject: [PATCH 4/8] Moving around data --- R/sysdata.rda | Bin 4395323 -> 4400068 bytes R/toxEval.R | 20 +++----------------- inst/extdata/pCodeInfo.RData | Bin 3553 -> 3700 bytes 3 files changed, 3 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z;dIp}#sc!+Q~8dZDVPORt?`=g!;_@{g5HttfzCHReDLUm>GwCRDg0!A1Ab3--f`)E zdFVUK_pbZkWcvlbr{h0G@ju`*pX1U!zvG>@M^5|p$@WWS{Nc+RP5mQxSI^JLgL|xk zp0(_R8+Tgte|Yw$%}qz1gWGKQ5Nkds8h^O{TC0&V-wJ?(Ut`I4;NA~jLC>o&Uha3e zd&z|2@MU|$yY^P~ixdA#EI&rJ8~v<14>Z=idc$zf`SG;2Gvym;;&ry7zi5#`*a6TM9j{LLj z^{d}y$+6deWY;ZbLp*Y$9sf<1p3eSrgB9P%o0go&9{XHswdp=A&&TPv?e97(J`U`& z;L86$LsPe}&PzGD=(Ac1r`Tx{sUVz{%1T9pXaRw2NK3l3deHbfypkOAG{_g($hif{ z{N`NN`cr8ex5&i}X=;%PDKC!HeAk@ From c7a74780bb945b4fe17b3c1596973ef81411b4e5 Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Thu, 3 Nov 2016 17:45:01 -0500 Subject: [PATCH 5/8] Moving around data --- man/pCodeInfo.Rd | 3 +++ man/passiveData.Rd | 11 ----------- man/wData.Rd | 11 ----------- 3 files changed, 3 insertions(+), 22 deletions(-) delete mode 100644 man/passiveData.Rd delete mode 100644 man/wData.Rd diff --git a/man/pCodeInfo.Rd b/man/pCodeInfo.Rd index f607d670..1625c1bc 100644 --- a/man/pCodeInfo.Rd +++ b/man/pCodeInfo.Rd @@ -7,5 +7,8 @@ \description{ pCodeInfo } +\examples{ +head(pCodeInfo) +} \keyword{datasets} diff --git a/man/passiveData.Rd b/man/passiveData.Rd deleted file mode 100644 index 31444269..00000000 --- a/man/passiveData.Rd +++ /dev/null @@ -1,11 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/toxEval.R -\docType{data} -\name{passiveData} -\alias{passiveData} -\title{passiveData} -\description{ -passiveData -} -\keyword{datasets} - diff --git a/man/wData.Rd b/man/wData.Rd deleted file mode 100644 index d17bc888..00000000 --- a/man/wData.Rd +++ /dev/null @@ -1,11 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/toxEval.R -\docType{data} -\name{wData} -\alias{wData} -\title{wData} -\description{ -wData -} -\keyword{datasets} - From 7831fab516a88f857391a0c22eddf889d32ce33d Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Fri, 4 Nov 2016 12:23:31 -0500 Subject: [PATCH 6/8] Fix order on x axis --- R/sysdata.rda | Bin 4400068 -> 4400020 bytes 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zb#i2@xOeN+jjg_+kn5CH;{)L7h&?(s&t=5@BZASfq!fc=pAkLa;zEGikd8p1bOcmH zv(yVOb#%Sb(S3NPYjEa9VSr^(^N=?LRYYD>+_oUBY7tfeWYrJI`U|;n<>;EwV7-B` zP>6mCf$c46`_v1sb{ybm_J?N&J^=>;fk6WSSlw~mc+sbM0LuZ3 z_v$A=IKNSCKmW+Nk;XH78zVOk2xqMuCdli1h!Kbp`s6fOJEO=k`~6^b>x7H{X`b~q z07VV~8l41;8q%SL7T!&NHj>&JnMu@%VXH=IVC3(Kkw@~3fZiRLu+8HEeN`X&>hE6K z#{&Ng0fPUG2()Shy8Q6q?190^B$FFy39J4KLqOiuyovco*qymuqTu;Q)wHrj#iht& z15@qS4O2b-S`vVI2v9!(!uCeDefH?>E>sugu_Egnz5oAw>El22pFa8bEnocn6aV?E z(hEno{m{#|u6*>rzVTa+{o(abKNMsWjv@O|n@5N)`!N0&+oyApblJ7ie}yZn8V_cv z)hv_#SMA%pM{M Date: Fri, 4 Nov 2016 12:38:43 -0500 Subject: [PATCH 7/8] levels for x axis --- inst/shiny/server.R | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/inst/shiny/server.R b/inst/shiny/server.R index 1725a697..01b414df 100644 --- a/inst/shiny/server.R +++ b/inst/shiny/server.R @@ -823,8 +823,10 @@ shinyServer(function(input, output,session) { filter(shortName %in% unique(graphData$site)) if(all(siteLimits$shortName %in% sitesOrdered)){ + graphData <- mutate(graphData, site = factor(site, levels = sitesOrdered[sitesOrdered %in% siteLimits$shortName])) siteLimits <- mutate(siteLimits, shortName = factor(shortName, levels=sitesOrdered[sitesOrdered %in% siteLimits$shortName])) } else { + graphData <- mutate(graphData, site = factor(site, levels = unique(site))) siteLimits <- mutate(siteLimits, shortName = factor(shortName)) } @@ -860,7 +862,7 @@ shinyServer(function(input, output,session) { geom_tile(aes(x = site, y=reorderedCat, fill=meanEAR)) + theme(axis.text.x = element_text(colour=siteLimits$lakeColor, angle = 90,vjust=0.5,hjust = 1)) + - scale_x_discrete(limits=levels(siteLimits$shortName),drop=FALSE) + + # scale_x_discrete(limits=levels(siteLimits$shortName),drop=FALSE) + ylab("") + xlab("") + labs(fill=paste(ifelse(meanEARlogic, "Mean","Maximum")," EAR")) + @@ -882,7 +884,7 @@ shinyServer(function(input, output,session) { geom_tile(aes(x = site, y=reorderedCat, fill=meanEAR)) + theme(axis.text.x = element_text(colour=siteLimits$lakeColor, angle = 90,vjust=0.5,hjust = 1)) + - scale_x_discrete(limits=levels(siteLimits$shortName),drop=FALSE) + + # scale_x_discrete(limits=levels(siteLimits$shortName),drop=FALSE) + ylab("") + xlab("") + labs(fill=paste(ifelse(meanEARlogic, "Mean","Maximum")," EAR")) + From a34fa4243c6b8c388ba7e1caa9110a2c7cb7684d Mon Sep 17 00:00:00 2001 From: Laura DeCicco Date: Fri, 4 Nov 2016 12:39:13 -0500 Subject: [PATCH 8/8] version update --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index ed92f378..a9f23c36 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: toxEval Type: Package Title: ToxCast Evaluations -Version: 0.2.3 +Version: 0.2.4 Date: 2016-10-19 Authors@R: c( person("Steven", "Corsi", role = c("aut"), email = "srcorsi@usgs.gov"),

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