Merge pull request #110 from PF2-pasteur-fr/development

hvaret · web-flow · commit 66b4b3d0249b · 2025-10-09T15:18:11.000+02:00
Development
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,9 +1,12 @@
 Package: SARTools
 Type: Package
 Title: Statistical Analysis of RNA-Seq Tools
-Version: 1.8.1
-Date: 2022-03-23
-Author: Marie-Agnes Dillies and Hugo Varet
+Version: 1.8.2
+Date: 2025-10-09
+Authors@R: c(
+    person(given = "Hugo", family = "Varet", role = c("aut", "cre"), email = "hugo.varet@pasteur.fr"),
+    person(given = "Marie-Agnès", family = "Dillies", role = c("aut"), email = "marie-agnes.dillies@pasteur.fr")
+  )
 Maintainer: Hugo Varet <hugo.varet@pasteur.fr>
 Depends: R (>= 3.3.0),
 	DESeq2 (>= 1.32.0),
@@ -19,7 +22,6 @@ Imports: genefilter (>= 1.44.0),
 	grDevices,
 	grid,
 	gridExtra,
-	knitr,
 	limma,
 	rlang,
 	rmarkdown (>= 1.4),
@@ -28,10 +30,10 @@ Imports: genefilter (>= 1.44.0),
 	stats,
 	SummarizedExperiment,
 	utils
-Suggests: optparse
+Suggests: knitr, optparse
 biocViews: Software
 VignetteBuilder: knitr, rmarkdown
 Encoding: latin1
 Description: Provide R tools and an environment for the statistical analysis of RNA-Seq projects: load and clean data, produce figures, perform statistical analysis/testing with DESeq2 or edgeR, export results and create final report.
 License: GPL-2
-RoxygenNote: 7.1.2
+RoxygenNote: 7.3.2
diff --git a/NEWS b/NEWS
@@ -1,3 +1,9 @@
+CHANGES IN VERSION 1.8.2
+------------------------
+	o use of after_stat(density) instead of ..density..
+	o fixed other few deprecated usages of ggplot2
+	o back to default DESeq2 shrinkage as "ashr" tends to produce aberrant log2FoldChanges
+
 CHANGES IN VERSION 1.8.1
 ------------------------
 	o log2FoldChanges from DESeq2 are now computed using lfcShrink() with type="ashr" as "apeglm"
diff --git a/R/SARTools-package.r b/R/SARTools-package.r
@@ -1,6 +1,5 @@
 #' Provide R tools and an environment for the statistical analysis of RNA-Seq projects: load and clean data, produce figures, perform statistical analysis/testing with DESeq2 or edgeR, export results and create final report
 #' @title Statistical Analysis of RNA-Seq Tools
 #' @author Marie-Agnes Dillies and Hugo Varet
-#' @docType package
 #' @name SARTools-package
-NULL
+"_PACKAGE"
diff --git a/R/barplotNull.R b/R/barplotNull.R
@@ -25,6 +25,6 @@ barplotNull <- function(counts, group, col=c("lightblue","orange","MediumVioletR
             ggplot_theme +
             theme(axis.text.x=element_text(angle=90, hjust=1, vjust=0.5)) +
             scale_y_continuous(expand=expansion(mult=c(0.01, 0.05))) +
-            geom_hline(yintercept=percentage.allNull, linetype="dashed", color="black", size=1))
+            geom_hline(yintercept=percentage.allNull, linetype="dashed", color="black", linewidth=1))
   if (outfile) dev.off()
 }
diff --git a/R/countsBoxplots.R b/R/countsBoxplots.R
@@ -11,7 +11,7 @@
 #' @author Marie-Agnes Dillies and Hugo Varet
 
 countsBoxplots <- function(object, group, col = c("lightblue","orange","MediumVioletRed","SpringGreen"), outfile=TRUE, ggplot_theme=theme_gray()){
-  if (class(object)=="DESeqDataSet"){
+  if (inherits(object, "DESeqDataSet")){
     counts <- counts(object)
     counts <- removeNull(counts)
     norm.counts <- counts(object, normalized=TRUE)
diff --git a/R/diagSizeFactorsPlots.R b/R/diagSizeFactorsPlots.R
@@ -31,7 +31,7 @@ diagSizeFactorsPlots <- function(dds, group, col=c("lightblue","orange","MediumV
         xlab(expression(log[2]~(counts/geometric~mean))) +
         ylab("") +
         ggtitle(paste0("Size factor diagnostic - ", samples[j])) +
-        geom_vline(xintercept=log2(sizeFactors(dds)[j]), linetype="dashed", color="red", size=1) +
+        geom_vline(xintercept=log2(sizeFactors(dds)[j]), linetype="dashed", color="red", linewidth=1) +
         ggplot_theme
     }
     tmpfun <- function(...) grid.arrange(..., nrow=nrow, ncol=ncol)
diff --git a/R/dispersionsPlot.R b/R/dispersionsPlot.R
@@ -43,7 +43,7 @@ dispersionsPlot <- function(dds, outfile=TRUE, ggplot_theme=theme_gray()){
   disp <- disp[disp>1e-8]
   d <- data.frame(disp)
   p2 <- ggplot(data=d, aes(x=.data$disp)) +
-    geom_histogram(bins=80, aes(y=.data$..density..)) +
+    geom_histogram(bins=80, aes(y=after_stat(density))) +
     scale_x_continuous(trans = log10_trans(),
                        breaks = trans_breaks("log10", function(x) 10^x),
                        labels = trans_format("log10", math_format())) +
diff --git a/R/exploreCounts.R b/R/exploreCounts.R
@@ -14,12 +14,12 @@
 exploreCounts <- function(object, group, typeTrans="VST", gene.selection="pairwise",
                           col=c("lightblue","orange","MediumVioletRed","SpringGreen"),
                           ggplot_theme=theme_light()){
-  if (class(object)=="DESeqDataSet"){
+  if (inherits(object, "DESeqDataSet")){
     if (typeTrans == "VST") counts.trans <- assay(varianceStabilizingTransformation(object))
     else counts.trans <- assay(rlogTransformation(object))
     PCAPlot(counts.trans=counts.trans, group=group, col=col, ggplot_theme=ggplot_theme)
     clusterPlot(counts.trans=counts.trans, group=group, ggplot_theme=ggplot_theme)  
-  } else if (class(object)=="DGEList"){
+  } else if (inherits(object, "DGEList")){
     MDSPlot(dge=object, group=group, col=col, gene.selection=gene.selection, ggplot_theme=ggplot_theme)
     clusterPlot(counts.trans=cpm(object, prior.count=2, log=TRUE), group=group, ggplot_theme=ggplot_theme)  
   } else{
diff --git a/R/pairwiseScatterPlots.R b/R/pairwiseScatterPlots.R
@@ -20,7 +20,7 @@ pairwiseScatterPlots <- function(counts, outfile=TRUE, ggplot_theme=theme_gray()
       for (j in 1:ncol){
         if (i==j) next
         if (i > j){
-          p[[k]] <- ggplot(data=cbind(d, z=1), aes_string(x=names(d)[i], y=names(d)[j], z="z")) +
+          p[[k]] <- ggplot(data=cbind(d, z=1), aes(x=.data[[names(d)[i]]], y=.data[[names(d)[j]]], z=.data[["z"]])) +
             stat_summary_2d(fun=function(z) log(sum(z)), bins=60, show.legend=FALSE) +
             scale_x_continuous(trans = log10_trans(),
                                breaks = trans_breaks("log10", function(x) 10^x),
diff --git a/R/run.DESeq2.r b/R/run.DESeq2.r
@@ -34,7 +34,7 @@ run.DESeq2 <- function(counts, target, varInt, batch=NULL,
   dds <- estimateDispersions(dds, fitType=fitType)
   
   # statistical testing: perform all the comparisons between the levels of varInt
-  dds <- nbinomWaldTest(dds, ...)
+  dds <- nbinomWaldTest(dds, betaPrior=TRUE, ...)
   results <- list()
   for (comp in combn(nlevels(colData(dds)[,varInt]), 2, simplify=FALSE)){
     levelRef <- levels(colData(dds)[,varInt])[comp[1]]
@@ -43,10 +43,6 @@ run.DESeq2 <- function(counts, target, varInt, batch=NULL,
                    contrast=c(varInt, levelTest, levelRef),
                    pAdjustMethod=pAdjustMethod, cooksCutoff=cooksCutoff,
                    independentFiltering=independentFiltering, alpha=alpha)
-    lfcs <- lfcShrink(dds, res=res,
-                      contrast=c(varInt, levelTest, levelRef),
-                      type="ashr", quiet=TRUE)
-    res$log2FoldChange <- lfcs$log2FoldChange
     results[[paste0(levelTest,"_vs_",levelRef)]] <- res
     cat(paste("Comparison", levelTest, "vs", levelRef, "done\n"))
   }
diff --git a/inst/report_DESeq2.rmd b/inst/report_DESeq2.rmd
@@ -226,8 +226,6 @@ Figure 14 shows the volcano plots for the comparisons performed and differential
 
 </center>
 
-Note that the log2(Fold-Changes) are shrunk using the "ashr" method that has been shown to be more robust than the original "normal" method [@ashr].
-
 Full results as well as lists of differentially expressed features are provided in the following text files which can be easily read in a spreadsheet. For each comparison:
 
 - TestVsRef.complete.txt contains results for all the features;
diff --git a/man/SARTools-package.Rd b/man/SARTools-package.Rd
diff --git a/man/loadCountData.Rd b/man/loadCountData.Rd
diff --git a/template_script_DESeq2.r b/template_script_DESeq2.r
@@ -2,7 +2,7 @@
 ### R script to compare several conditions with the SARTools and DESeq2 packages
 ### Hugo Varet
 ### March 23rd, 2022
-### designed to be executed with SARTools 1.8.1
+### designed to be executed with SARTools 1.8.2
 ################################################################################
 
 ################################################################################
diff --git a/template_script_DESeq2_CL.r b/template_script_DESeq2_CL.r
@@ -2,7 +2,7 @@
 ### R script to compare several conditions with the SARTools and DESeq2 packages
 ### Hugo Varet
 ### March 23rd, 2022
-### designed to be executed with SARTools 1.8.1
+### designed to be executed with SARTools 1.8.2
 ### run "Rscript template_script_DESeq2_CL.r --help" to get some help
 ################################################################################
 
diff --git a/template_script_edgeR.r b/template_script_edgeR.r
@@ -2,7 +2,7 @@
 ### R script to compare several conditions with the SARTools and edgeR packages
 ### Hugo Varet
 ### March 23rd, 2022
-### designed to be executed with SARTools 1.8.1
+### designed to be executed with SARTools 1.8.2
 ################################################################################
 
 ################################################################################
diff --git a/template_script_edgeR_CL.r b/template_script_edgeR_CL.r
@@ -2,7 +2,7 @@
 ### R script to compare several conditions with the SARTools and edgeR packages
 ### Hugo Varet
 ### March 23rd, 2022
-### designed to be executed with SARTools 1.8.1
+### designed to be executed with SARTools 1.8.2
 ### run "Rscript template_script_edgeR_CL.r --help" to get some help
 ################################################################################
 

Original file line number	Diff line number	Diff line change
`@@ -25,6 +25,6 @@ barplotNull <- function(counts, group, col=c("lightblue","orange","MediumVioletR`
`25`	`25`	`ggplot_theme +`
`26`	`26`	`theme(axis.text.x=element_text(angle=90, hjust=1, vjust=0.5)) +`
`27`	`27`	`scale_y_continuous(expand=expansion(mult=c(0.01, 0.05))) +`
`28`		`- geom_hline(yintercept=percentage.allNull, linetype="dashed", color="black", size=1))`
	`28`	`+ geom_hline(yintercept=percentage.allNull, linetype="dashed", color="black", linewidth=1))`
`29`	`29`	`if (outfile) dev.off()`
`30`	`30`	`}`
Original file line number	Diff line number	Diff line change
`@@ -31,7 +31,7 @@ diagSizeFactorsPlots <- function(dds, group, col=c("lightblue","orange","MediumV`
`31`	`31`	`xlab(expression(log[2]~(counts/geometric~mean))) +`
`32`	`32`	`ylab("") +`
`33`	`33`	`ggtitle(paste0("Size factor diagnostic - ", samples[j])) +`
`34`		`- geom_vline(xintercept=log2(sizeFactors(dds)[j]), linetype="dashed", color="red", size=1) +`
	`34`	`+ geom_vline(xintercept=log2(sizeFactors(dds)[j]), linetype="dashed", color="red", linewidth=1) +`
`35`	`35`	`ggplot_theme`
`36`	`36`	`}`
`37`	`37`	`tmpfun <- function(...) grid.arrange(..., nrow=nrow, ncol=ncol)`