update

.Rbuildignore

@@ -1,12 +1,13 @@
-^enONE\.Rproj$
-^\.Rproj\.user$
-^LICENSE\.md$
-^README\.Rmd$
-^doc$
-^Meta$
-^_pkgdown\.yml$
-^docs$
-^pkgdown$
-^\.github$
-^vignettes/data$
-^data$
+^enONE\.Rproj$
+^\.Rproj\.user$
+^LICENSE\.md$
+^README\.Rmd$
+^doc$
+^Meta$
+^_pkgdown\.yml$
+^docs$
+^pkgdown$
+^cran-comments.md$
+^\.github$
+^vignettes/data$
+^data$

.github/workflows/rhub.yaml

@@ -37,10 +37,14 @@ jobs:
       with:
         config: ${{ github.event.inputs.config }}
       id: rhub-setup
-
+
+    - uses: r-lib/actions/setup-r@v2
+      with:
+        use-public-rspm: true
+
     - uses: r-lib/actions/setup-r-dependencies@v2
       with:
-        extra-packages: any::pkgdown, local::., any::rcmdcheck, any::XML
+        extra-packages: local::., any::rcmdcheck, any::XML
         needs: website
 
     - name: Install dependencies

DESCRIPTION

@@ -27,7 +27,6 @@ Imports:
     paintingr,
     pbapply,
     plotly,
-    rlang,
     rstatix,
     S4Vectors,
     stats,
@@ -36,6 +35,8 @@ Imports:
     tibble
 Suggests: 
     knitr,
-    rmarkdown
+    patchwork,
+    rmarkdown,
+    tidyr
 VignetteBuilder: knitr
 URL: https://thereallda.github.io/enONE/

cran-comments.md

@@ -1,11 +1,11 @@
-## Test environments
-
--   R-hub windows-x86_64-release, R release
--   R-hub macos-highsierra-release, R release
--   R-hub ubuntu-gcc-release, R release
-
-## R CMD check results
-
-There were no ERRORs, WARNINGs or NOTEs.
-
-
+## Test environments
+
+-   R-hub windows-x86_64-release, R release
+-   R-hub macos-highsierra-release, R release
+-   R-hub ubuntu-gcc-release, R release
+
+## R CMD check results
+
+There were no ERRORs, WARNINGs or NOTEs.
+
+

vignettes/enONE_tutorial-zh.Rmd

@@ -34,11 +34,25 @@ knitr::opts_chunk$set(
 
 *Figure: Schematic workflow for total RNAs from PBMCs and three sets of spike-ins.*
 
+通过以下代码下载原始数据。
+
+```{r,warning=FALSE}
+# create directory for data
+dir.create("data/")
+options(timeout = max(6000, getOption("timeout")))
+# download Counts.csv
+download.file("https://figshare.com/ndownloader/files/46250704", destfile = "data/Counts.csv")
+# download metadata.csv
+download.file("https://figshare.com/ndownloader/files/46251412", destfile = "data/metadata.csv")
+```
+
 我们首先读取数据，包括基因表达量的count matrix和样本信息的metadata。matrix和样本信息的。metadata至少包括两列，即用于样本生物分组的"condition"列和用于样本富集分组的"enrich"列。
 
 ```{r,warning=FALSE,message=FALSE}
 library(enONE)
-library(tidyverse)
+library(dplyr)
+library(ggplot2)
+library(tidyr)
 library(patchwork)
 
 # read in metadata and counts matrix
@@ -339,7 +353,7 @@ syn_level <- synEnrichment(Enone, method=norm.method, log=TRUE)
 
 # transform to long format
 syn_df <- as.data.frame(syn_level) %>% 
-  rownames_to_column("syn_id") %>% 
+  tibble::rownames_to_column("syn_id") %>% 
   pivot_longer(cols = -syn_id,
                names_to = "id",
                values_to = "logFC") %>% 

vignettes/enONE_tutorial.Rmd

@@ -38,12 +38,26 @@ Notably, we included three types of spike-in RNAs:
 
 *Figure: Schematic workflow for total RNAs from PBMCs and three sets of spike-ins.*
 
+Raw data for this tutorial can be downloaded with the following code.
+
+```{r,warning=FALSE}
+# create directory for data
+dir.create("data/")
+options(timeout = max(6000, getOption("timeout")))
+# download Counts.csv
+download.file("https://figshare.com/ndownloader/files/46250704", destfile = "data/Counts.csv")
+# download metadata.csv
+download.file("https://figshare.com/ndownloader/files/46251412", destfile = "data/metadata.csv")
+```
+
 We start by reading in the data, including count matrix and metadata. metadata should include at lease two columns, namely the `condition` column for biological grouping of samples, and the `enrich` column for enrichment grouping of samples. 
 
 
 ```{r,warning=FALSE,message=FALSE}
 library(enONE)
-library(tidyverse)
+library(dplyr)
+library(ggplot2)
+library(tidyr)
 library(patchwork)
 
 # read in metadata and counts matrix
@@ -352,7 +366,7 @@ syn_level <- synEnrichment(Enone, method=norm.method, log=TRUE)
 
 # transform to long format
 syn_df <- as.data.frame(syn_level) %>% 
-  rownames_to_column("syn_id") %>% 
+  tibble::rownames_to_column("syn_id") %>% 
   pivot_longer(cols = -syn_id,
                names_to = "id",
                values_to = "logFC") %>%