Made changes in assign_job_queue.R, cleanup.R, lineage.R, msa.R, tree.R

NAMESPACE

@@ -247,6 +247,7 @@ importFrom(shiny,showNotification)
 importFrom(stats,as.formula)
 importFrom(stats,complete.cases)
 importFrom(stats,logLik)
+importFrom(stats,median)
 importFrom(stats,na.omit)
 importFrom(stringi,stri_extract_all_regex)
 importFrom(stringi,stri_replace_all_regex)
@@ -276,6 +277,7 @@ importFrom(tidyr,replace_na)
 importFrom(tidyr,separate)
 importFrom(tidyr,unite)
 importFrom(utils,combn)
+importFrom(utils,globalVariables)
 importFrom(viridis,scale_fill_viridis)
 importFrom(visNetwork,visEdges)
 importFrom(visNetwork,visGroups)

R/assign_job_queue.R

@@ -92,7 +92,8 @@ mapAdvOption2Process <- function(advanced_opts) {
 #'
 #' @importFrom dplyr across everything select summarise
 #' @importFrom rlang warn abort inform
-#'
+#' @importFrom stats median
+#' 
 #' @return [list] names: processes; values: median runtime (seconds)
 #'
 #' see molevol_scripts/R/metrics.R for info on functions called here
@@ -210,7 +211,7 @@ writeProcessRuntime2TSV <- function(dir_job_results, filepath) {
         names_to = "process",
         values_to = "median_seconds"
       ) |>
-      dplyr::arrange(dplyr::desc(median_seconds))
+      dplyr::arrange(dplyr::desc(.data$median_seconds))
 
     # Write the resulting tibble to a TSV file
     readr::write_tsv(df_proc_medians, file = filepath)

R/globals.R

@@ -0,0 +1,4 @@
+# File to put all data.table variables that aren't defined otherwise
+
+#' @importFrom utils globalVariables
+utils::globalVariables(c("Protein"))

R/lineage.R

@@ -395,10 +395,10 @@ IPG2Lineage <- function(accessions, ipg_file,
     {
         # browser()
         acc <- accessions[i]
-        acc_inds <- which(mergedTax$Protein == acc)
+        acc_inds <- which(.data$mergedTax$Protein == acc)
         if (length(acc_inds) != 0) {
             # refseq inds take precedence
-            refseq_inds <- acc_inds[which(mergedTax[acc_inds, ]$Source == "RefSeq")]
+            refseq_inds <- acc_inds[which(.data$mergedTax[acc_inds, ]$Source == "RefSeq")]
             if (length(refseq_inds) != 0) {
                 # Take the first first row of the refseq (smallest index)
                 refseq_rows[i] <- refseq_inds[1]
@@ -424,15 +424,15 @@ IPG2Lineage <- function(accessions, ipg_file,
     }
     if (length(genbank_rows) != 0) {
         genbank_ipg_dt <- ipg_dt[genbank_rows, ]
-        genbank_lins <- GCA2Lineage(gca_ipg_dt,
+        genbank_lins <- GCA2Lineage(.data$gca_ipg_dt,
             assembly_path = genbank_assembly_path,
             lineagelookup_path
         )
     }
 
 
     lins <- GCA2Lineage(prot_data = ipg_dt, assembly_path, lineagelookup_path)
-    lins <- lins[!is.na(Lineage)] %>% unique()
+    lins <- lins[!is.na(.data$Lineage)] %>% unique()
 
     return(lins)
 }

R/msa.R

@@ -196,7 +196,7 @@ createMSA_PDF <- function(fasta_path, out_path = NULL,
 #' will be saved.
 #'
 #' @importFrom Biostrings readAAStringSet
-#'
+#' 
 #' @return A list containing the alignment object and the output file path.
 #' @export
 #'

R/tree.R

@@ -59,9 +59,6 @@
 convertFA2Tree <- function(fa_path = here("data/alns/pspa_snf7.fa"),
     tre_path = here("data/alns/pspa_snf7.tre"),
     fasttree_path = here("src/FastTree")) {
-    # fa_path=here("data/alns/pspa_snf7.fa")
-    # tre_path=here("data/alns/pspa_snf7.tre")
-    # fasttree_path=here("src/FastTree")
 
     # Check if the FASTA file exists
     if (!file.exists(fa_path)) {
@@ -89,7 +86,7 @@ convertFA2Tree <- function(fa_path = here("data/alns/pspa_snf7.fa"),
     message(fa_path)
     system2(
         command = fasttree_path,
-        args = paste(c(fa_path, ">", tre_path),
+        args = paste(c(fa_path, ">", .data$tre_path),
             sep = "", collapse = " "
         )
     )