R/DEAnalyzer.R
In scfurl/probedeeper: Making the Analysis of Microarray Data More Efficient
####DEAnalyzer####
autoLIMMA2DEAnalyzer<-function(limmalist, index.sel){
InputGeneLists<-list()
for(i in 1:length(index.sel)){
InputGeneLists[[i]]<-rownames(limmalist[[3]][[index.sel[i]]])
names(InputGeneLists)[i]<-limmalist[[2]][[index.sel[i]]][1]
}
new("DEAnalyzerInput", InputGeneSet=InputGeneLists,
DEData=limmalist[[4]][index.sel])
}
Input2DEAnalyzer<-function(InputGeneLists, DEData){
new("DEAnalyzerInput", InputGeneSet=InputGeneLists,
DEData=DEData)
}
CalcDEAnalyzer<-function(object, GOopt=TRUE, PWopt=TRUE){
if(class(object)!="DEAnalyzerInput")stop("Input problem")
calc.object<-new("DEAnalyzerCalcs")
calc.object@InputGeneSet<-object@InputGeneSet
calc.object@DEData<-object@DEData
calc.object@ObjectInfo<-list(NumberGeneSets<-length(object@InputGeneSet),
ContainsGOData=GOopt, ContainsPWData=PWopt)
for(i in 1:length(object@InputGeneSet)){
FC<-object@DEData[[i]]$logFC[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
PVal<-object@DEData[[i]]$adj.P.Val[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
Symbol<-rownames(object@DEData[[i]])[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
names(FC)<-Symbol
names(PVal)<-Symbol
calc.object@FoldChange[[i]]<-FC
calc.object@Pvalues[[i]]<-PVal
UpDnCV<-vector()
UpDnCV[calc.object@FoldChange[[i]]>0]<-"Up"
UpDnCV[calc.object@FoldChange[[i]]<0]<-"Dn"
calc.object@UpDnClassvec[[i]]<-as.factor(UpDnCV)
Updf<-data.frame(Symbol=as.character(names(calc.object@FoldChange[[i]])[calc.object@FoldChange[[i]]>0]),
logFC=calc.object@FoldChange[[i]][calc.object@FoldChange[[i]]>0],
Pvalue=calc.object@Pvalues[[i]][calc.object@FoldChange[[i]]>0], stringsAsFactors=FALSE)
Dndf<-data.frame(Symbol=names(calc.object@FoldChange[[i]])[calc.object@FoldChange[[i]]<0],
logFC=calc.object@FoldChange[[i]][calc.object@FoldChange[[i]]<0],
Pvalue=calc.object@Pvalues[[i]][calc.object@FoldChange[[i]]<0], stringsAsFactors=FALSE)
colnames(Updf)<-c("Symbol", "logFC", "adj.P.Val")
colnames(Dndf)<-c("Symbol", "logFC", "adj.P.Val")
calc.object@Up[[i]]<-Updf
calc.object@Down[[i]]<-Dndf
names(calc.object@Up)[i]<-names(object@InputGeneSet[i])
names(calc.object@Down)[i]<-names(object@InputGeneSet[i])
#names(calc.object@Up[[i]]$Pvalue)<-calc.object@Up[[i]]$Symbol
#names(calc.object@Down[[i]]$Pvalue)<-calc.object@Down[[i]]$Symbol
if(GOopt==TRUE){
# allGenes.Up<-object@DEData[[i]]$adj.P.Val[object@DEData[[i]]$logFC>0]
# allGenes.Dn<-object@DEData[[i]]$adj.P.Val[object@DEData[[i]]$logFC<0]
# names(allGenes.Up)<-rownames(object@DEData[[i]][object@DEData[[i]]$logFC>0,])
# names(allGenes.Dn)<-rownames(object@DEData[[i]][object@DEData[[i]]$logFC<0,])
#calc.object@GO.UP[[i]]<-runGO(allGenes=allGenes, geneSel=calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"])
#calc.object@GO.DN[[i]]<-runGO(allGenes=allGenes, geneSel=calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"])
#calc.object@GO.UP[[i]]<-runGO(allGenes=allGenes.Up)
#calc.object@GO.DN[[i]]<-runGO(allGenes=allGenes.Dn)
allGenes.Up<-rep(0,length=nrow(calc.object@DEData[[i]]))
allGenes.Up[rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"])]<-1
allGenes.Up[!(rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"]))]<-0
names(allGenes.Up)<-rownames(calc.object@DEData[[i]])
allGenes.Dn<-rep(0,length=nrow(calc.object@DEData[[i]]))
allGenes.Dn[rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"])]<-1
allGenes.Dn[!(rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"]))]<-0
names(allGenes.Dn)<-rownames(calc.object@DEData[[i]])
calc.object@GO.BP.UP[[i]]<-runGO(allGenes=allGenes.Up, ont="BP")
calc.object@GO.BP.DN[[i]]<-runGO(allGenes=allGenes.Dn, ont="BP")
calc.object@GO.MF.UP[[i]]<-runGO(allGenes=allGenes.Up, ont="MF")
calc.object@GO.MF.DN[[i]]<-runGO(allGenes=allGenes.Dn, ont="MF")
names(calc.object@GO.BP.UP)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.BP.DN)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.MF.UP)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.MF.DN)[i]<-names(object@InputGeneSet[i])
}
}
if(PWopt==TRUE){
calc.object<-runDAVID(calc.object)
}
return(calc.object)
}
topDiffGenes<-function(allScore){
return(allScore < 0.05)
}
includeGenes<-function(allGenes){
return(allGenes==1)
}
runGO<-function(allGenes, ont){
if(length(allGenes)>5){
includeGenes(allGenes)
GOdata <- new("topGOdata",
description = "NoRxvHC", ontology = ont,
allGenes = allGenes, geneSel = includeGenes,
annot = annFUN.org, mapping="org.Hs.eg.db", ID="symbol")
#resultFisher <- runTest(GOdata, algorithm = "classic", statistic = "fisher")
#resultKS <- runTest(GOdata, algorithm = "classic", statistic = "ks")
resultKS.elim <- runTest(GOdata, algorithm = "elim", statistic = "ks")
Results<-GenTable(GOdata, topNodes = (length(GOdata@graph@nodes)/10),
elimKS = resultKS.elim,
orderBy = "elimKS")
return(Results)}
else{
return("NA")
}
}
runDAVID<-function(object){
david<-DAVIDWebService(email="sfurlan@uw.edu", url="https://david.ncifcrf.gov/webservice/services/DAVIDWebService.DAVIDWebServiceHttpSoap12Endpoint/")
if(length(object@Up)>0){
for(i in 1:length(object@Up)){
df<-data.frame()
print(paste("Obtaining pathway data for genes upregulated in ", names(object@InputGeneSet)[i],sep=""))
if(nrow(object@Up[[i]])>0){
e2s = toTable(org.Hs.egSYMBOL)
result<-addList(david, e2s$gene_id[e2s$symbol %in% object@Up[[i]]$Symbol],
idType="ENTREZ_GENE_ID",
listName=paste(names(object@InputGeneSet)[i], ".UP", sep=""), listType="Gene")
setAnnotationCategories(david, c("PANTHER_PATHWAY","BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
}
if(length(df$Genes)>0){
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
if(nrow(object@Up[[i]])==0){
df[1,1]<-"No genes to perform pathway analysis"
}
if(nrow(df)==0){
df[1,1]<-"No pathways found"
}
object@PW.UP[[i]]<-df
names(object@PW.UP)[i]<-names(object@InputGeneSet)[i]
}
}
if(length(object@Down)>0){
for(i in 1:length(object@Down)){
df<-data.frame()
print(paste("Obtaining pathway data for genes downregulated in ", names(object@InputGeneSet)[i],sep=""))
if(nrow(object@Down[[i]])>0){
e2s = toTable(org.Hs.egSYMBOL)
result<-addList(david, e2s$gene_id[e2s$symbol %in% object@Down[[i]]$Symbol],
idType="ENTREZ_GENE_ID",
listName=paste(names(object@InputGeneSet)[i], ".DN", sep=""), listType="Gene")
setAnnotationCategories(david, c("PANTHER_PATHWAY","BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
}
if(length(df$Genes)>0){
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
if(nrow(object@Down[[i]])==0){
df[1,1]<-"No genes to perform pathway analysis"
}
if(nrow(df)==0){
df[1,1]<-"No pathways found"
}
object@PW.DN[[i]]<-df
names(object@PW.DN)[i]<-names(object@InputGeneSet)[i]
}
}
return(object)
}
writeDEAnalyzer<-function(object, directory="", cellStyle="", IPAopt=TRUE){
if(directory!="") {
wd<-getwd()
newpath<-paste(wd,"/",directory, sep="")
dir.create(newpath, showWarnings=FALSE)
}
files<-c("-GenesUP.xls","-GenesDN.xls", "-GenesALL.xls")
if(object@ObjectInfo$ContainsGOData==TRUE){
files<-c(files, "-GOTermsUP-BP.xls","-GOTermsDN-BP.xls", "-GOTermsUP-MF.xls","-GOTermsDN-MF.xls")
}
if(object@ObjectInfo$ContainsPWData==TRUE){
files<-c(files, "-PathwaysUP.xls","-PathwaysDN.xls")
}
#data.ind<-c("-GenesUP.xls","-GenesDN.xls", "-GOTermsUP.xls","-GOTermsDN.xls", "-PathwaysUP.xls","-PathwaysDN.xls") %in% files
prefix<-format(Sys.Date(), format="%Y%m%d")
if(directory!="") {
location<-paste(directory, "/",sep="")
filename<-prefix
}
else {
filename<-prefix
location<-""
}
if(IPAopt==TRUE){
if(directory!="") {
newpath<-paste(newpath,"/IPA", sep="")
dir.create(newpath, showWarnings=FALSE)
IPAlocation<-paste(location, "IPA/", sep="")
}
else{IPAlocation<-"IPA/"}
}
wb<-list()
for(j in 1:length(files)){
wb[[j]]<-loadWorkbook(filename=paste(location, filename, files[j], sep=""), create=TRUE)
}
for(i in 1:length(object@InputGeneSet)){
dflist<-list(Genesup.df<-object@Up[[i]],
Genesdn.df<-object@Down[[i]], Genesall.df<-rbind(object@Up[[i]], object@Down[[i]]))
if(object@ObjectInfo$ContainsGOData==TRUE){
dflist<-c(dflist,
list(dflistGOup.df<-object@GO.BP.UP[[i]]), list(GOdn.df<-object@GO.BP.DN[[i]]),
list(dflistGOup.df<-object@GO.MF.UP[[i]]), list(GOdn.df<-object@GO.MF.DN[[i]]))
}
if(object@ObjectInfo$ContainsPWData==TRUE){
dflist<-c(dflist, list(dflistPWup.df<-object@PW.UP[[i]]), list(PWdn.df<-object@PW.DN[[i]]))
}
if(IPAopt==TRUE){
IPAout<-cbind(rownames(object@DEData[[i]]), object@DEData[[i]][,c(1,5)])
colnames(IPAout)<-c("Symbol", "Log.Ratio", "Adj.P.Val")
write.table(IPAout, file=paste(IPAlocation, filename, "-", names(object@InputGeneSet)[i], ".txt", sep=""), sep="\t", quote=FALSE, row.names=FALSE)
}
for(j in 1:length(files)){
createSheet(wb[[j]], name = names(object@InputGeneSet)[i])
writeWorksheet(wb[[j]], dflist[[j]], sheet=names(object@InputGeneSet)[i])
# if(class(cellstyle)!="character"){
# createCellStyle(wb[[j]], "GeneData")
# setCellStyle(wb[[j]], sheet =names(object@InputGeneSet)[i], row =1 , col =1 , cellstyle =cellStyle)
# }
saveWorkbook(wb[[j]])
}
}
}
quickXL<-function(filename=paste(format(Sys.Date(), format="%Y_%m_%d_"), format(Sys.time(), format="%H_%M"), ".xls", sep=""), obj, sheetname="1"){
if(class(obj)!="data.frame"){stop("Only data frames supported")}
wb<-loadWorkbook(filename=filename, create=TRUE)
createSheet(wb, name = sheetname)
obj2<-cbind(rownames(obj),obj)
colnames(obj2)<-c("Symbol", colnames(obj))
writeWorksheet(wb, obj2, sheet=sheetname)
saveWorkbook(wb)
}
quickXL.list<-function(filename=NULL, obj, header=FALSE, rownames=TRUE, method=c("openxlsx", "XLConnect"), overwrite=F){
if(class(obj)!="list"){
obj<-list(Sheet1=obj)
}
if(is.null(filename)){stop("Invalid filename")}
method<-match.arg(method)
if(method=="XLConnect"){
wb<-XLConnect::loadWorkbook(filename=filename, create=TRUE)
for(i in names(obj)){
XLConnect::createSheet(wb, name=substring(i, 1, 30))
dat<-obj[[i]]
if(rownames==TRUE){
rowN<-ifelse(header==TRUE, c("", rownames(dat)), rownames(dat))
}
else
{rowN<-NULL}
XLConnect::writeWorksheet(wb, dat, sheet=substring(i, 1, 30), header=header, rownames=rowN)
}
XLConnect::saveWorkbook(wb)
message("Workbook Written")
}
if(method=="openxlsx"){
hs1 <- openxlsx::createStyle(fgFill = "#DCE6F1", halign = "CENTER", textDecoration = "italic",
border = "Bottom")
wb<-openxlsx::createWorkbook()
for(i in names(obj)){
openxlsx::addWorksheet(wb, sheetName=substring(i, 1, 30))
dat<-obj[[i]]
if(rownames==TRUE){
rowN<-ifelse(header==TRUE, c("", rownames(dat)), rownames(dat))
}else{
rowN<-NULL}
openxlsx::writeData(wb=wb, x=dat, sheet=substring(i, 1, 30), headerStyle = hs1)
}
openxlsx::saveWorkbook(wb, file=filename, overwrite = overwrite)
message("Workbook Written")
}
}
readautoLIMMA<-function(limmalist){
toprint<-paste(1:length(as.character(limmalist[[2]][1,])), as.character(limmalist[[2]][1,]), sep="-")
return(toprint)
}
autoDAVID<-function(vector, input="symbol"){
if(!input %in% c("symbol", "ENS")){stop("Input Not Correct")}
library(org.Hs.eg.db)
david<-DAVIDWebService(email="sfurlan@uw.edu", url="https://david.ncifcrf.gov/webservice/services/DAVIDWebService.DAVIDWebServiceHttpSoap12Endpoint/")
if(input=="symbol"){
e2s = toTable(org.Hs.egSYMBOL)
foundgenes<-e2s$gene_id[e2s$symbol %in% vector]
result<-RDAVIDWebService::addList(david, foundgenes,
idType="ENTREZ_GENE_ID",
listName="autoDavid", listType="Gene")
found<-length(foundgenes)
print(paste("Found ", found, " Annotated Genes of ", length(vector), " Submitted", sep=""))
}
if(input=="ENS"){
e2s <- toTable(org.Hs.egENSEMBL)
foundgenes<-e2s$gene_id[e2s$ensembl_id %in% vector]
result<-RDAVIDWebService::addList(david, foundgenes,
idType="ENTREZ_GENE_ID",
listName="autoDavid", listType="Gene")
found<-length(foundgenes)
print(paste("Found ", found, " Annotated Genes of ", length(vector), " Submitted", sep=""))
}
RDAVIDWebService::setAnnotationCategories(david, c("BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-RDAVIDWebService::getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
if(input=="ENS"){
if(length(df$Genes)>0)
{
e2s2 = toTable(org.Hs.egSYMBOL)
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s2$symbol[e2s2$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
}
if(input=="symbol"){
if(length(df$Genes)>0)
{
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
}
return(df)
}
GroupSelection<-function(classvec, SelectionIndex, data, alldata, cols, method="separate"){
selected<<-levels(classvec)[SelectionIndex]
data.sel<<-data[,classvec %in% selected]
classvec.sel<<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<<-alldata[,classvec %in% selected]
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<<-gcolor[classvec.sel]
tcolors<<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
limma.master<<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
limma.alldata<<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
# return(invisible(limma.master))
# return(invisible(limma.alldata))
# return(invisible(gcolors))
# return(invisible(tcolors))
# return(invisible(tcolor))
# return(invisible(gcolor))
# return(invisible(data.sel))
# return(invisible(alldata.sel))
# return(invisible(classvec.sel))
}
GroupSelectionNoLimma<-function(classvec, SelectionIndex, data, alldata, cols){
selected<<-levels(classvec)[SelectionIndex]
data.sel<<-data[,classvec %in% selected]
classvec.sel<<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<<-alldata[,classvec %in% selected]
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<<-gcolor[classvec.sel]
tcolors<<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
# limma.master<<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH")
# limma.alldata<<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH")
# # return(invisible(limma.master))
# return(invisible(limma.alldata))
# return(invisible(gcolors))
# return(invisible(tcolors))
# return(invisible(tcolor))
# return(invisible(gcolor))
# return(invisible(data.sel))
# return(invisible(alldata.sel))
# return(invisible(classvec.sel))
}
GroupSelectionLocal<-function(suff=".new", classvec, SelectionIndex, data, alldata, cols, method="separate"){
selected<-levels(classvec)[SelectionIndex]
data.sel<-data[,classvec %in% selected]
classvec.sel<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<-alldata[,classvec %in% selected]
assign(paste("selected", suff, sep=""), selected, envir=.GlobalEnv)
assign(paste("data.sel", suff, sep=""), data.sel, envir=.GlobalEnv)
assign(paste("classvec.sel", suff, sep=""), classvec.sel, envir=.GlobalEnv)
assign(paste("alldata.sel", suff, sep=""), alldata.sel, envir=.GlobalEnv)
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
gcolor<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<-gcolor[classvec.sel]
tcolors<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
limma.master<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
limma.alldata<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
assign(paste("gcolor", suff, sep=""), gcolor, envir=.GlobalEnv)
assign(paste("tcolor", suff, sep=""), tcolor, envir=.GlobalEnv)
assign(paste("gcolors", suff, sep=""), gcolors, envir=.GlobalEnv)
assign(paste("tcolors", suff, sep=""), tcolors, envir=.GlobalEnv)
assign(paste("limma.master", suff, sep=""), limma.master, envir=.GlobalEnv)
assign(paste("limma.alldata", suff, sep=""), limma.alldata, envir=.GlobalEnv)
}
#debug(AssignColors)
AssignColors<-function(classvec, cols){
selected<-levels(classvec)
colmatch<-lapply(cols, "[", match(selected,cols$group))
#names(colmatch)<-cols[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
#gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(selected)), col=colmatch$cols, labels=colmatch$group)
#tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
#gcolors<<-gcolor[classvec]
#tcolors<<-tcolor[classvec[classvec!="Healthy.Control"]]
return(colmatch)
}
PDViolin<-function(obj, gene){
obj.class<-class(obj)
}
scfurl/probedeeper documentation built on May 29, 2019, 3:25 p.m.
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####DEAnalyzer####
autoLIMMA2DEAnalyzer<-function(limmalist, index.sel){
InputGeneLists<-list()
for(i in 1:length(index.sel)){
InputGeneLists[[i]]<-rownames(limmalist[[3]][[index.sel[i]]])
names(InputGeneLists)[i]<-limmalist[[2]][[index.sel[i]]][1]
}
new("DEAnalyzerInput", InputGeneSet=InputGeneLists,
DEData=limmalist[[4]][index.sel])
}
Input2DEAnalyzer<-function(InputGeneLists, DEData){
new("DEAnalyzerInput", InputGeneSet=InputGeneLists,
DEData=DEData)
}
CalcDEAnalyzer<-function(object, GOopt=TRUE, PWopt=TRUE){
if(class(object)!="DEAnalyzerInput")stop("Input problem")
calc.object<-new("DEAnalyzerCalcs")
calc.object@InputGeneSet<-object@InputGeneSet
calc.object@DEData<-object@DEData
calc.object@ObjectInfo<-list(NumberGeneSets<-length(object@InputGeneSet),
ContainsGOData=GOopt, ContainsPWData=PWopt)
for(i in 1:length(object@InputGeneSet)){
FC<-object@DEData[[i]]$logFC[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
PVal<-object@DEData[[i]]$adj.P.Val[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
Symbol<-rownames(object@DEData[[i]])[rownames(object@DEData[[i]]) %in% object@InputGeneSet[[i]]]
names(FC)<-Symbol
names(PVal)<-Symbol
calc.object@FoldChange[[i]]<-FC
calc.object@Pvalues[[i]]<-PVal
UpDnCV<-vector()
UpDnCV[calc.object@FoldChange[[i]]>0]<-"Up"
UpDnCV[calc.object@FoldChange[[i]]<0]<-"Dn"
calc.object@UpDnClassvec[[i]]<-as.factor(UpDnCV)
Updf<-data.frame(Symbol=as.character(names(calc.object@FoldChange[[i]])[calc.object@FoldChange[[i]]>0]),
logFC=calc.object@FoldChange[[i]][calc.object@FoldChange[[i]]>0],
Pvalue=calc.object@Pvalues[[i]][calc.object@FoldChange[[i]]>0], stringsAsFactors=FALSE)
Dndf<-data.frame(Symbol=names(calc.object@FoldChange[[i]])[calc.object@FoldChange[[i]]<0],
logFC=calc.object@FoldChange[[i]][calc.object@FoldChange[[i]]<0],
Pvalue=calc.object@Pvalues[[i]][calc.object@FoldChange[[i]]<0], stringsAsFactors=FALSE)
colnames(Updf)<-c("Symbol", "logFC", "adj.P.Val")
colnames(Dndf)<-c("Symbol", "logFC", "adj.P.Val")
calc.object@Up[[i]]<-Updf
calc.object@Down[[i]]<-Dndf
names(calc.object@Up)[i]<-names(object@InputGeneSet[i])
names(calc.object@Down)[i]<-names(object@InputGeneSet[i])
#names(calc.object@Up[[i]]$Pvalue)<-calc.object@Up[[i]]$Symbol
#names(calc.object@Down[[i]]$Pvalue)<-calc.object@Down[[i]]$Symbol
if(GOopt==TRUE){
# allGenes.Up<-object@DEData[[i]]$adj.P.Val[object@DEData[[i]]$logFC>0]
# allGenes.Dn<-object@DEData[[i]]$adj.P.Val[object@DEData[[i]]$logFC<0]
# names(allGenes.Up)<-rownames(object@DEData[[i]][object@DEData[[i]]$logFC>0,])
# names(allGenes.Dn)<-rownames(object@DEData[[i]][object@DEData[[i]]$logFC<0,])
#calc.object@GO.UP[[i]]<-runGO(allGenes=allGenes, geneSel=calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"])
#calc.object@GO.DN[[i]]<-runGO(allGenes=allGenes, geneSel=calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"])
#calc.object@GO.UP[[i]]<-runGO(allGenes=allGenes.Up)
#calc.object@GO.DN[[i]]<-runGO(allGenes=allGenes.Dn)
allGenes.Up<-rep(0,length=nrow(calc.object@DEData[[i]]))
allGenes.Up[rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"])]<-1
allGenes.Up[!(rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Up"]))]<-0
names(allGenes.Up)<-rownames(calc.object@DEData[[i]])
allGenes.Dn<-rep(0,length=nrow(calc.object@DEData[[i]]))
allGenes.Dn[rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"])]<-1
allGenes.Dn[!(rownames(calc.object@DEData[[i]]) %in% names(calc.object@Pvalues[[i]][calc.object@UpDnClassvec[[i]]=="Dn"]))]<-0
names(allGenes.Dn)<-rownames(calc.object@DEData[[i]])
calc.object@GO.BP.UP[[i]]<-runGO(allGenes=allGenes.Up, ont="BP")
calc.object@GO.BP.DN[[i]]<-runGO(allGenes=allGenes.Dn, ont="BP")
calc.object@GO.MF.UP[[i]]<-runGO(allGenes=allGenes.Up, ont="MF")
calc.object@GO.MF.DN[[i]]<-runGO(allGenes=allGenes.Dn, ont="MF")
names(calc.object@GO.BP.UP)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.BP.DN)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.MF.UP)[i]<-names(object@InputGeneSet[i])
names(calc.object@GO.MF.DN)[i]<-names(object@InputGeneSet[i])
}
}
if(PWopt==TRUE){
calc.object<-runDAVID(calc.object)
}
return(calc.object)
}
topDiffGenes<-function(allScore){
return(allScore < 0.05)
}
includeGenes<-function(allGenes){
return(allGenes==1)
}
runGO<-function(allGenes, ont){
if(length(allGenes)>5){
includeGenes(allGenes)
GOdata <- new("topGOdata",
description = "NoRxvHC", ontology = ont,
allGenes = allGenes, geneSel = includeGenes,
annot = annFUN.org, mapping="org.Hs.eg.db", ID="symbol")
#resultFisher <- runTest(GOdata, algorithm = "classic", statistic = "fisher")
#resultKS <- runTest(GOdata, algorithm = "classic", statistic = "ks")
resultKS.elim <- runTest(GOdata, algorithm = "elim", statistic = "ks")
Results<-GenTable(GOdata, topNodes = (length(GOdata@graph@nodes)/10),
elimKS = resultKS.elim,
orderBy = "elimKS")
return(Results)}
else{
return("NA")
}
}
runDAVID<-function(object){
david<-DAVIDWebService(email="sfurlan@uw.edu", url="https://david.ncifcrf.gov/webservice/services/DAVIDWebService.DAVIDWebServiceHttpSoap12Endpoint/")
if(length(object@Up)>0){
for(i in 1:length(object@Up)){
df<-data.frame()
print(paste("Obtaining pathway data for genes upregulated in ", names(object@InputGeneSet)[i],sep=""))
if(nrow(object@Up[[i]])>0){
e2s = toTable(org.Hs.egSYMBOL)
result<-addList(david, e2s$gene_id[e2s$symbol %in% object@Up[[i]]$Symbol],
idType="ENTREZ_GENE_ID",
listName=paste(names(object@InputGeneSet)[i], ".UP", sep=""), listType="Gene")
setAnnotationCategories(david, c("PANTHER_PATHWAY","BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
}
if(length(df$Genes)>0){
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
if(nrow(object@Up[[i]])==0){
df[1,1]<-"No genes to perform pathway analysis"
}
if(nrow(df)==0){
df[1,1]<-"No pathways found"
}
object@PW.UP[[i]]<-df
names(object@PW.UP)[i]<-names(object@InputGeneSet)[i]
}
}
if(length(object@Down)>0){
for(i in 1:length(object@Down)){
df<-data.frame()
print(paste("Obtaining pathway data for genes downregulated in ", names(object@InputGeneSet)[i],sep=""))
if(nrow(object@Down[[i]])>0){
e2s = toTable(org.Hs.egSYMBOL)
result<-addList(david, e2s$gene_id[e2s$symbol %in% object@Down[[i]]$Symbol],
idType="ENTREZ_GENE_ID",
listName=paste(names(object@InputGeneSet)[i], ".DN", sep=""), listType="Gene")
setAnnotationCategories(david, c("PANTHER_PATHWAY","BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
}
if(length(df$Genes)>0){
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
if(nrow(object@Down[[i]])==0){
df[1,1]<-"No genes to perform pathway analysis"
}
if(nrow(df)==0){
df[1,1]<-"No pathways found"
}
object@PW.DN[[i]]<-df
names(object@PW.DN)[i]<-names(object@InputGeneSet)[i]
}
}
return(object)
}
writeDEAnalyzer<-function(object, directory="", cellStyle="", IPAopt=TRUE){
if(directory!="") {
wd<-getwd()
newpath<-paste(wd,"/",directory, sep="")
dir.create(newpath, showWarnings=FALSE)
}
files<-c("-GenesUP.xls","-GenesDN.xls", "-GenesALL.xls")
if(object@ObjectInfo$ContainsGOData==TRUE){
files<-c(files, "-GOTermsUP-BP.xls","-GOTermsDN-BP.xls", "-GOTermsUP-MF.xls","-GOTermsDN-MF.xls")
}
if(object@ObjectInfo$ContainsPWData==TRUE){
files<-c(files, "-PathwaysUP.xls","-PathwaysDN.xls")
}
#data.ind<-c("-GenesUP.xls","-GenesDN.xls", "-GOTermsUP.xls","-GOTermsDN.xls", "-PathwaysUP.xls","-PathwaysDN.xls") %in% files
prefix<-format(Sys.Date(), format="%Y%m%d")
if(directory!="") {
location<-paste(directory, "/",sep="")
filename<-prefix
}
else {
filename<-prefix
location<-""
}
if(IPAopt==TRUE){
if(directory!="") {
newpath<-paste(newpath,"/IPA", sep="")
dir.create(newpath, showWarnings=FALSE)
IPAlocation<-paste(location, "IPA/", sep="")
}
else{IPAlocation<-"IPA/"}
}
wb<-list()
for(j in 1:length(files)){
wb[[j]]<-loadWorkbook(filename=paste(location, filename, files[j], sep=""), create=TRUE)
}
for(i in 1:length(object@InputGeneSet)){
dflist<-list(Genesup.df<-object@Up[[i]],
Genesdn.df<-object@Down[[i]], Genesall.df<-rbind(object@Up[[i]], object@Down[[i]]))
if(object@ObjectInfo$ContainsGOData==TRUE){
dflist<-c(dflist,
list(dflistGOup.df<-object@GO.BP.UP[[i]]), list(GOdn.df<-object@GO.BP.DN[[i]]),
list(dflistGOup.df<-object@GO.MF.UP[[i]]), list(GOdn.df<-object@GO.MF.DN[[i]]))
}
if(object@ObjectInfo$ContainsPWData==TRUE){
dflist<-c(dflist, list(dflistPWup.df<-object@PW.UP[[i]]), list(PWdn.df<-object@PW.DN[[i]]))
}
if(IPAopt==TRUE){
IPAout<-cbind(rownames(object@DEData[[i]]), object@DEData[[i]][,c(1,5)])
colnames(IPAout)<-c("Symbol", "Log.Ratio", "Adj.P.Val")
write.table(IPAout, file=paste(IPAlocation, filename, "-", names(object@InputGeneSet)[i], ".txt", sep=""), sep="\t", quote=FALSE, row.names=FALSE)
}
for(j in 1:length(files)){
createSheet(wb[[j]], name = names(object@InputGeneSet)[i])
writeWorksheet(wb[[j]], dflist[[j]], sheet=names(object@InputGeneSet)[i])
# if(class(cellstyle)!="character"){
# createCellStyle(wb[[j]], "GeneData")
# setCellStyle(wb[[j]], sheet =names(object@InputGeneSet)[i], row =1 , col =1 , cellstyle =cellStyle)
# }
saveWorkbook(wb[[j]])
}
}
}
quickXL<-function(filename=paste(format(Sys.Date(), format="%Y_%m_%d_"), format(Sys.time(), format="%H_%M"), ".xls", sep=""), obj, sheetname="1"){
if(class(obj)!="data.frame"){stop("Only data frames supported")}
wb<-loadWorkbook(filename=filename, create=TRUE)
createSheet(wb, name = sheetname)
obj2<-cbind(rownames(obj),obj)
colnames(obj2)<-c("Symbol", colnames(obj))
writeWorksheet(wb, obj2, sheet=sheetname)
saveWorkbook(wb)
}
quickXL.list<-function(filename=NULL, obj, header=FALSE, rownames=TRUE, method=c("openxlsx", "XLConnect"), overwrite=F){
if(class(obj)!="list"){
obj<-list(Sheet1=obj)
}
if(is.null(filename)){stop("Invalid filename")}
method<-match.arg(method)
if(method=="XLConnect"){
wb<-XLConnect::loadWorkbook(filename=filename, create=TRUE)
for(i in names(obj)){
XLConnect::createSheet(wb, name=substring(i, 1, 30))
dat<-obj[[i]]
if(rownames==TRUE){
rowN<-ifelse(header==TRUE, c("", rownames(dat)), rownames(dat))
}
else
{rowN<-NULL}
XLConnect::writeWorksheet(wb, dat, sheet=substring(i, 1, 30), header=header, rownames=rowN)
}
XLConnect::saveWorkbook(wb)
message("Workbook Written")
}
if(method=="openxlsx"){
hs1 <- openxlsx::createStyle(fgFill = "#DCE6F1", halign = "CENTER", textDecoration = "italic",
border = "Bottom")
wb<-openxlsx::createWorkbook()
for(i in names(obj)){
openxlsx::addWorksheet(wb, sheetName=substring(i, 1, 30))
dat<-obj[[i]]
if(rownames==TRUE){
rowN<-ifelse(header==TRUE, c("", rownames(dat)), rownames(dat))
}else{
rowN<-NULL}
openxlsx::writeData(wb=wb, x=dat, sheet=substring(i, 1, 30), headerStyle = hs1)
}
openxlsx::saveWorkbook(wb, file=filename, overwrite = overwrite)
message("Workbook Written")
}
}
readautoLIMMA<-function(limmalist){
toprint<-paste(1:length(as.character(limmalist[[2]][1,])), as.character(limmalist[[2]][1,]), sep="-")
return(toprint)
}
autoDAVID<-function(vector, input="symbol"){
if(!input %in% c("symbol", "ENS")){stop("Input Not Correct")}
library(org.Hs.eg.db)
david<-DAVIDWebService(email="sfurlan@uw.edu", url="https://david.ncifcrf.gov/webservice/services/DAVIDWebService.DAVIDWebServiceHttpSoap12Endpoint/")
if(input=="symbol"){
e2s = toTable(org.Hs.egSYMBOL)
foundgenes<-e2s$gene_id[e2s$symbol %in% vector]
result<-RDAVIDWebService::addList(david, foundgenes,
idType="ENTREZ_GENE_ID",
listName="autoDavid", listType="Gene")
found<-length(foundgenes)
print(paste("Found ", found, " Annotated Genes of ", length(vector), " Submitted", sep=""))
}
if(input=="ENS"){
e2s <- toTable(org.Hs.egENSEMBL)
foundgenes<-e2s$gene_id[e2s$ensembl_id %in% vector]
result<-RDAVIDWebService::addList(david, foundgenes,
idType="ENTREZ_GENE_ID",
listName="autoDavid", listType="Gene")
found<-length(foundgenes)
print(paste("Found ", found, " Annotated Genes of ", length(vector), " Submitted", sep=""))
}
RDAVIDWebService::setAnnotationCategories(david, c("BIOCARTA", "REACTOME_PATHWAY","KEGG_PATHWAY"))
Table<-RDAVIDWebService::getFunctionalAnnotationChart(david)
df<-data.frame(Table@.Data, stringsAsFactors=FALSE)
colnames(df)<-(Table@names)
if(input=="ENS"){
if(length(df$Genes)>0)
{
e2s2 = toTable(org.Hs.egSYMBOL)
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s2$symbol[e2s2$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
}
if(input=="symbol"){
if(length(df$Genes)>0)
{
for(j in 1:length(df$Genes)){
df$Genes[j]<-paste(e2s$symbol[e2s$gene_id %in% unlist(strsplit(df$Genes[j], ", "))], collapse=", ")
}
}
}
return(df)
}
GroupSelection<-function(classvec, SelectionIndex, data, alldata, cols, method="separate"){
selected<<-levels(classvec)[SelectionIndex]
data.sel<<-data[,classvec %in% selected]
classvec.sel<<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<<-alldata[,classvec %in% selected]
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<<-gcolor[classvec.sel]
tcolors<<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
limma.master<<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
limma.alldata<<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
# return(invisible(limma.master))
# return(invisible(limma.alldata))
# return(invisible(gcolors))
# return(invisible(tcolors))
# return(invisible(tcolor))
# return(invisible(gcolor))
# return(invisible(data.sel))
# return(invisible(alldata.sel))
# return(invisible(classvec.sel))
}
GroupSelectionNoLimma<-function(classvec, SelectionIndex, data, alldata, cols){
selected<<-levels(classvec)[SelectionIndex]
data.sel<<-data[,classvec %in% selected]
classvec.sel<<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<<-alldata[,classvec %in% selected]
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<<-gcolor[classvec.sel]
tcolors<<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
# limma.master<<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH")
# limma.alldata<<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH")
# # return(invisible(limma.master))
# return(invisible(limma.alldata))
# return(invisible(gcolors))
# return(invisible(tcolors))
# return(invisible(tcolor))
# return(invisible(gcolor))
# return(invisible(data.sel))
# return(invisible(alldata.sel))
# return(invisible(classvec.sel))
}
GroupSelectionLocal<-function(suff=".new", classvec, SelectionIndex, data, alldata, cols, method="separate"){
selected<-levels(classvec)[SelectionIndex]
data.sel<-data[,classvec %in% selected]
classvec.sel<-as.factor(as.character(classvec[classvec %in% selected]))
alldata.sel<-alldata[,classvec %in% selected]
assign(paste("selected", suff, sep=""), selected, envir=.GlobalEnv)
assign(paste("data.sel", suff, sep=""), data.sel, envir=.GlobalEnv)
assign(paste("classvec.sel", suff, sep=""), classvec.sel, envir=.GlobalEnv)
assign(paste("alldata.sel", suff, sep=""), alldata.sel, envir=.GlobalEnv)
colnames(alldata.sel)<-make.unique(as.character(classvec.sel))
colmatch<-cols$cols[match(selected,cols$group)]
names(colmatch)<-cols$group[match(selected,cols$group)]
gcolor<-colmatch[order(names(colmatch))]
pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
tcolor<-gcolor[names(gcolor)!="Healthy.Control"]
gcolors<-gcolor[classvec.sel]
tcolors<-tcolor[classvec[classvec.sel!="Healthy.Control"]]
limma.master<-autoLIMMA(data.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
limma.alldata<-autoLIMMA(alldata.sel, classvec.sel, element1=seq(1, length(levels(classvec.sel))), element2=seq(1, length(levels(classvec.sel))), pvalue.thresh=0.05, lfc.thresh=0.5, adjust.method="BH", method=method)
assign(paste("gcolor", suff, sep=""), gcolor, envir=.GlobalEnv)
assign(paste("tcolor", suff, sep=""), tcolor, envir=.GlobalEnv)
assign(paste("gcolors", suff, sep=""), gcolors, envir=.GlobalEnv)
assign(paste("tcolors", suff, sep=""), tcolors, envir=.GlobalEnv)
assign(paste("limma.master", suff, sep=""), limma.master, envir=.GlobalEnv)
assign(paste("limma.alldata", suff, sep=""), limma.alldata, envir=.GlobalEnv)
}
#debug(AssignColors)
AssignColors<-function(classvec, cols){
selected<-levels(classvec)
colmatch<-lapply(cols, "[", match(selected,cols$group))
#names(colmatch)<-cols[match(selected,cols$group)]
#pie(rep(1,length(colmatch)), col=colmatch, labels=names(colmatch))
#gcolor<<-colmatch[order(names(colmatch))]
pie(rep(1,length(selected)), col=colmatch$cols, labels=colmatch$group)
#tcolor<<-gcolor[names(gcolor)!="Healthy.Control"]
#gcolors<<-gcolor[classvec]
#tcolors<<-tcolor[classvec[classvec!="Healthy.Control"]]
return(colmatch)
}
PDViolin<-function(obj, gene){
obj.class<-class(obj)
}
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