Removed deprecated ggplot code, changed default values for assembly a…

…nd normlization

DESCRIPTION

@@ -13,8 +13,8 @@ Authors@R: c(
     role = c("aut")),
     person("Fabian", "Mueller", email = "[email protected]",
     role = c("aut", "cre")))
-Date: 2024-01-25
-Version: 2.21.1
+Date: 2024-03-19
+Version: 2.21.2
 Suggests:
     Category,
     GOstats,

R/agePrediction.R

@@ -503,7 +503,7 @@ add.quantile.plot <- function(report, object, actualAges, predictedAges){
 	density.frame <- data.frame(Difference=density$x,Density=density$y)
 	median <- median(diff)
 
-	plot <- ggplot(data,aes(x=Difference,y=0.0))+geom_density(aes(y=..density..))+geom_point(aes(label=Sample))+geom_text(aes(label=Sample),hjust=.5,vjust=1.5,size=3,colour='#BE1E2D')+geom_area(data=subset(density.frame,Difference>=q1 & Difference<=q99),aes(x=Difference,y=Density),fill='#75BC1C')+geom_area(data=subset(density.frame,Difference<=q1),aes(x=Difference,y=Density),fill='#BE1E2D')+geom_area(data=subset(density.frame,Difference>=q99),aes(x=Difference,y=Density),fill='#BE1E2D')+geom_vline(xintercept=median)+ylab("Density")
+	plot <- ggplot(data,aes(x=Difference,y=0.0))+geom_density(aes(y=after_stat(density)))+geom_point(aes(label=Sample))+geom_text(aes(label=Sample),hjust=.5,vjust=1.5,size=3,colour='#BE1E2D')+geom_area(data=subset(density.frame,Difference>=q1 & Difference<=q99),aes(x=Difference,y=Density),fill='#75BC1C')+geom_area(data=subset(density.frame,Difference<=q1),aes(x=Difference,y=Density),fill='#BE1E2D')+geom_area(data=subset(density.frame,Difference>=q99),aes(x=Difference,y=Density),fill='#BE1E2D')+geom_vline(xintercept=median)+ylab("Density")
 	report.plot <- createReportPlot("age_prediction_quantile", report)
 	print(plot)
 	report.plot <- off(report.plot)
@@ -612,7 +612,7 @@ add.age.histogram <- function(report,ages){
 	data <- data.frame(Age=ages)
 	colors <- rnb.getOption("colors.category")
 	gradient <- rnb.getOption("colors.gradient")
-	plot <- ggplot(data,aes(x=Age))+geom_histogram(aes(fill=..count..,y=..density..),binwidth=5) +geom_density(color=colors[2])+scale_fill_gradient(low=gradient[1],high=gradient[2],name="Count")+ylab("Density")
+	plot <- ggplot(data,aes(x=Age))+geom_histogram(aes(fill=after_stat(count),y=after_stat(density)),binwidth=5) +geom_density(color=colors[2])+scale_fill_gradient(low=gradient[1],high=gradient[2],name="Count")+ylab("Density")
 	report.plot <- createReportPlot("predicted_ages_histogram",report)
 	print(plot)
 	report.plot <- off(report.plot)

R/controlPlotsBiSeq.R

@@ -170,7 +170,7 @@ rnb.plot.biseq.coverage.hist<-function(
 	dframe<-data.frame(Coverage=covg.rnbs)
 	#TODO: cut after 95 percentile of coverage
 	pp <- ggplot(dframe, aes_string(x = "Coverage")) + coord_cartesian(xlim=c(0,max.covg))+ 
-		labs(x = "Coverage", y = "# CpGs") + geom_histogram(aes_string(y = "..count.."), binwidth = 10)
+		labs(x = "Coverage", y = "# CpGs") + geom_histogram(aes(y = after_stat(count)), binwidth = 10)
 
 	if(writeToFile) {
 		print(pp)

R/differentialVariability.R

@@ -720,7 +720,7 @@ create.diffMeth.diffVar.subsample <- function(df2p,dens.subsample,is.special=NUL
     pp <- rnb.message.plot("Could not assess density")
   } else {
     pp <- ggplot(df2p.sub) + aes_string(x=colnames(df2p)[1],y=colnames(df2p)[2]) + 
-      stat_density2d(geom="tile", fill=DENS.COLORS.LOW[1], aes(,alpha=..density..^0.25), contour=FALSE, n=dens.n, h=stable.h) +
+      stat_density2d(geom="tile", fill=DENS.COLORS.LOW[1], aes(alpha=after_stat(density)^0.25), contour=FALSE, n=dens.n, h=stable.h) +
       scale_alpha(range = c(0.0, 1),guide=FALSE) +
       geom_vline(xintercept = rank.cut.diffMeth,linetype='dotted') + geom_hline(yintercept = rank.cut.diffVar,linetype='dotted')+
       scale_color_manual(values=c(rnb.getOption("colors.category")[c(1,2,4)],DENS.COLORS.LOW[1]))
@@ -739,7 +739,6 @@ create.diffMeth.diffVar.subsample <- function(df2p,dens.subsample,is.special=NUL
         ss <- as.numeric(dens.subsample)
         if(nrow(df2p.special)>ss){
           pp <- pp + geom_point(data=df2p.special,aes_string(x=colnames(df2p)[1],y=colnames(df2p)[2],colour=colnames(df2p)[3]),size=0.4) + guides(fill=FALSE)
-          #pp <- pp + stat_density2d(data = df2p.special, geom="tile", aes(fill=colnames(df2p)[3],alpha=..density..^0.25), contour=FALSE, n =dens.n, h=stable.h)+scale_fill_manual(values=c(rnb.getOption("colors.category")[c(1,2,4)],DENS.COLORS.LOW[1]))
         }else{
           pp <- pp + geom_point(data=df2p.special,aes_string(x=colnames(df2p)[1],y=colnames(df2p)[2],colour=colnames(df2p)[3]),size=1) + guides(fill=FALSE)
         }

R/filtering.R

@@ -1229,7 +1229,7 @@ rnb.section.na.removal.internal <- function(report, dataset.class, numSamples, n
 				binwidth <- max((binwidth[2] - binwidth[1]) / 40, 1)
 				rplot <- createReportPlot(x$fname, report, width = 5, height = 5)
 				pp <- ggplot(dframe, aes_string(x = "x")) + labs(x = "Number of missing values", y = "Frequency") +
-					geom_histogram(aes_string(y = "..count.."), binwidth = binwidth)
+					geom_histogram(aes(y = after_stat(count)), binwidth = binwidth)
 				if (0 < threshold && threshold < 1) {
 					pp <- pp + geom_vline(xintercept = threshold * numSamples, linetype = "dotted")
 				}

R/plottingUtils.R

@@ -334,7 +334,7 @@ rnb.plot.beta.comparison <- function(beta.values, fprefix, report = NULL, qq.len
 	rplot <- createReportPlot(fnames[2], report, width = 6.8, height = 5.2)
 	pp <- ggplot(dframe, aes_string(x = "value")) + coord_cartesian(xlim = c(0, 1)) +
 		labs(x = expression(beta), y = "Density") +
-		geom_histogram(aes_string(y = "..density.."), binwidth = 0.02) +
+		geom_histogram(aes(y = after_stat(density)), binwidth = 0.02) +
 		facet_grid(vtype ~ .) + theme(plot.margin = pmargins)
 	print(pp)
 	off(rplot)
@@ -1467,7 +1467,7 @@ create.densityScatter <- function(df2p,is.special=NULL,dens.subsample=FALSE,dens
   		pp <- rnb.message.plot("Could not assess density")
   	} else {		
   		pp <- ggplot(df2p.sub) + aes_string(x=colnames(df2p)[1],y=colnames(df2p)[2]) + 
-		  stat_density2d(geom="tile", fill=DENS.COLORS.LOW[1], aes(,alpha=..density..^0.25), contour=FALSE, n=dens.n, h=stable.h) +
+		  stat_density2d(geom="tile", fill=DENS.COLORS.LOW[1], aes(alpha=after_stat(density)^0.25), contour=FALSE, n=dens.n, h=stable.h) +
 		  scale_alpha(range = c(0.0, 1))
 		if (sparse.points > 0){
 			if (sparse.points <= 1){

R/regionProfiles.R

@@ -203,7 +203,7 @@ rnb.plot.region.profile.density <- function(rnb.set, sample, region.type="", reg
 	stable.h <- c(stable.bandwidth.fun(df2p$relative.coord),stable.bandwidth.fun(df2p$meth))
 
 	pp <- ggplot(df2p) + aes(x=relative.coord,y=meth) + 
-		  stat_density2d(geom="tile",fill="#1F78B4", aes(alpha=..density..^0.25), contour = FALSE, h=stable.h) +
+		  stat_density2d(geom="tile",fill="#1F78B4", aes(alpha=after_stat(density)^0.25), contour = FALSE, h=stable.h) +
 		  ylim(0, 1) + ylab("methylation") + xlab("relative position") + theme(legend.position="none") +
 		  geom_vline(xintercept = c(0,1), linetype = "solid",size=1.5)
 	return(pp)

inst/extdata/RnBeadsDJ/app.R

@@ -42,13 +42,13 @@ RNB.MODULES.LOG.MSG <- c(
 	"exploratory_analysis"="Exploratory Analysis",
 	"differential_methylation"="Differential Methylation"
 )
-RNB.PLATFORMS <- c("Bisulfite Sequencing"="biseq", "Illumina EPIC"="illEpic", "Illumina EPIC v2"="illEpicv2", "Illumina 450k"="ill450k", "Illumina27k"="ill27k")
+RNB.PLATFORMS <- c("Bisulfite Sequencing"="biseq", "Illumina EPIC"="illEpic", "Illumina EPIC v2"="illEpicv2", "Illumina 450k"="ill450k", "Illumina27k"="ill27k", 'Illumina MMBC'='illMMBC')
 RNB.ASSEMBLIES <- rnb.get.assemblies()
 RNB.TABLE.SEPS <- c("comma" = ",", "tab"="\t")
 RNB.BED.STYLES <- c("BisSNP"="BisSNP", "ENCODE"="Encode", "EPP"="EPP", "Bismark cytosine"="bismarkCytosine", "Bismark coverage"="bismarkCov")
 RNB.FILTERING.SNP <- c("No filtering"="no", "3 SNPs"="3", "5 SNPs"="5", "Any SNPs"="any") ## TODO: Include SNPs MAF from the new hg38 annotation
-RNB.NORMALIZATION.METHODS=c("none", "bmiq", "illumina", "swan", "minfi.funnorm", "wm.dasen", "wm.nasen", "wm.betaqn", "wm.naten", "wm.nanet", "wm.nanes", "wm.danes", "wm.danet", "wm.danen", "wm.daten1", "wm.daten2", "wm.tost", "wm.fuks", "wm.swan")
-RNB.NORMALIZATION.BG.METHODS <- c("none", "methylumi.noob", "methylumi.goob", "enmix.oob")
+RNB.NORMALIZATION.METHODS=c("none", "bmiq", "illumina", "swan", "minfi.funnorm", "wm.dasen", "wm.nasen", "wm.betaqn", "wm.naten", "wm.nanet", "wm.nanes", "wm.danes", "wm.danet", "wm.danen", "wm.daten1", "wm.daten2", "wm.tost", "wm.fuks", "wm.swan", "scaling.internal")
+RNB.NORMALIZATION.BG.METHODS <- c("none", "methylumi.noob", "methylumi.goob", "enmix.oob", "sesame.noobsb")
 RNB.IMPUTATION.METHODS <- c("none", "mean.cpgs", "mean.samples", "random", "knn")
 RNB.TRACKHUB.FORMATS <- c("bigBed", "bigWig")
 RNB.SVA.NUM.METHODS <- c("leek", "be")
@@ -834,7 +834,7 @@ ui <- tagList(useShinyjs(), navbarPage(
 								tags$div(title=RNB.OPTION.DESC["normalization.method"], tags$code("normalization.method"))
 							),
 							tags$td(
-								selectInput("rnbOptsI.normalization.method", NULL, RNB.NORMALIZATION.METHODS, selected="wm.dasen")
+								selectInput("rnbOptsI.normalization.method", NULL, RNB.NORMALIZATION.METHODS, selected="scaling.internal")
 							),
 							tags$td(
 								verbatimTextOutput("rnbOptsO.normalization.method")
@@ -845,7 +845,7 @@ ui <- tagList(useShinyjs(), navbarPage(
 								tags$div(title=RNB.OPTION.DESC["normalization.background.method"], tags$code("normalization.background.method"))
 							),
 							tags$td(
-								selectInput("rnbOptsI.normalization.background.method", NULL, RNB.NORMALIZATION.BG.METHODS, selected="none")
+								selectInput("rnbOptsI.normalization.background.method", NULL, RNB.NORMALIZATION.BG.METHODS, selected="sesame.noobsb")
 							),
 							tags$td(
 								verbatimTextOutput("rnbOptsO.normalization.background.method")
@@ -1479,7 +1479,7 @@ server <- function(input, output, session) {
 			shinyjs::disable("rnbOptsI.normalization.background.method")
 			shinyjs::disable("rnbOptsI.exploratory.correlation.qc")
 		} else {
-			shinyjs::disable("rnbOptsI.assembly")
+			#shinyjs::disable("rnbOptsI.assembly")
 			shinyjs::disable("rnbOptsI.import.bed.style")
 			shinyjs::disable("rnbOptsI.filtering.coverage.threshold")
 			shinyjs::disable("rnbOptsI.filtering.low.coverage.masking")
@@ -1587,7 +1587,7 @@ server <- function(input, output, session) {
 	assemblySel <- reactive({
 		interfaceSetting <- input$rnbOptsI.assembly
 		res <- "hg19"
-		if (isBiseq() && !is.null(interfaceSetting)){
+		if (!is.null(interfaceSetting)){
 			res <- interfaceSetting
 		}
 		rnb.options(assembly=res)

inst/extdata/options.txt

@@ -2,7 +2,7 @@ Name	Type	Named	Null	Values	Default
 analysis.name	character	no	yes		NULL
 logging	logical	no	no		TRUE
 email	character	no	yes		NULL
-assembly	character	no	no		hg19
+assembly	character	no	no		hg38
 columns.pairing	integer.vector	yes	yes		NULL
 analyze.sites	logical	no	no		TRUE
 region.types	character.vector	no	yes		NULL
@@ -49,8 +49,8 @@ qc.cnv	logical	no	no		FALSE
 qc.cnv.refbased	logical	no	no		FALSE
 preprocessing	logical	no	no		TRUE
 normalization	logical	no	yes		NULL
-normalization.method	character	no	no	(none,scaling,scaling.internal,scaling.reference,bmiq,illumina,methylumi.illumina,swan,minfi.funnorm,wm.dasen,wm.nasen,wm.betaqn,wm.naten,wm.nanet,wm.nanes,wm.danes,wm.danet,wm.danen,wm.daten1,wm.daten2,wm.tost,wm.fuks,wm.swan)	wm.dasen
-normalization.background.method	character	no	no	(none,subtraction,sesame.noob,sesame.noobsb,methylumi.noob,methylumi.goob,enmix.oob)	none
+normalization.method	character	no	no	(none,scaling,scaling.internal,scaling.reference,bmiq,illumina,methylumi.illumina,swan,minfi.funnorm,wm.dasen,wm.nasen,wm.betaqn,wm.naten,wm.nanet,wm.nanes,wm.danes,wm.danet,wm.danen,wm.daten1,wm.daten2,wm.tost,wm.fuks,wm.swan)	scaling.internal
+normalization.background.method	character	no	no	(none,subtraction,sesame.noob,sesame.noobsb,methylumi.noob,methylumi.goob,enmix.oob)	sesame.noobsb
 normalization.plot.shifts	logical	no	no		TRUE
 filtering.whitelist	character	no	yes		NULL
 filtering.blacklist	character	no	yes		NULL