Hi,
I have 31 samples from three different breed groups where I am studying the effect of diet on breeds. I constructed multi-factor designs for DESeq2 and EdgeR as follows:
DESeq2:
EdgeR:
Could anyone please tell me what made such a big difference in results from two different programs? I would appreciate your help.
Thank you very much!
I have 31 samples from three different breed groups where I am studying the effect of diet on breeds. I constructed multi-factor designs for DESeq2 and EdgeR as follows:
countdata<-read.csv("htseq-merged_table.csv", row.names=1)
countdata<-countdata[1: (nrow(countdata)-5),]
sampleinfo<-read.csv("SampleTable_mod.csv")
sample<-sampleinfo$Sample
breed<-sampleinfo$Breed
diet<-sampleinfo$Diet
sampletable<-data.frame(Sample=sample, breed=breed, diet=diet)
countdata<-countdata[1: (nrow(countdata)-5),]
sampleinfo<-read.csv("SampleTable_mod.csv")
sample<-sampleinfo$Sample
breed<-sampleinfo$Breed
diet<-sampleinfo$Diet
sampletable<-data.frame(Sample=sample, breed=breed, diet=diet)
colnames(countdata)<-sampletable$Sample
ddsMat<-DESeqDataSetFromMatrix(countData=countdata, colData = sampletable, design = ~breed+diet+breed:diet )
dds<-DESeq(ddsMat)
resultsNames(dds)
#[1] "Intercept" "breedFIN" "breedTEX" "breedFXT" "dietFLU"
#[6] "dietCON" "breedFIN.dietFLU" "breedTEX.dietFLU" "breedFXT.dietFLU" "breedFIN.dietCON"
#[11] "breedTEX.dietCON" "breedFXT.dietCON"
FINTEXFlu<-results(dds, contrast=list("breedFIN.dietFLU","breedTEX.dietFLU"))
FINTEXFluSig<-subset(FINTEXFlu, padj < 0.1) #(36)
FINTEXFluSig<-FINTEXFluSig[abs(FINTEXFluSig$log2FoldChange) >=1,]
nrow(FINTEXFluSig)
25
ddsMat<-DESeqDataSetFromMatrix(countData=countdata, colData = sampletable, design = ~breed+diet+breed:diet )
dds<-DESeq(ddsMat)
resultsNames(dds)
#[1] "Intercept" "breedFIN" "breedTEX" "breedFXT" "dietFLU"
#[6] "dietCON" "breedFIN.dietFLU" "breedTEX.dietFLU" "breedFXT.dietFLU" "breedFIN.dietCON"
#[11] "breedTEX.dietCON" "breedFXT.dietCON"
FINTEXFlu<-results(dds, contrast=list("breedFIN.dietFLU","breedTEX.dietFLU"))
FINTEXFluSig<-subset(FINTEXFlu, padj < 0.1) #(36)
FINTEXFluSig<-FINTEXFluSig[abs(FINTEXFluSig$log2FoldChange) >=1,]
nrow(FINTEXFluSig)
25
EdgeR:
group<-factor(paste(breed, diet, sep="."))
ED<-DGEList(counts=countdata, group=group)
Y<-calcNormFactors(ED)
design<-model.matrix(~0+group)
colnames(design)<-levels(group)
Y<-estimateGLMCommonDisp(Y, verbose=TRUE)
Y<-estimateGLMTrendedDisp(Y, design)
Y<-estimateGLMTagwiseDisp(Y, design)
fit<-glmFit(Y, design)
mycontrast<-makeContrasts(FINF.TEXF=FIN.FLU-TEX.FLU, FINF.FXTF=FIN.FLU-FXT.FLU, TEXF.FXTF=TEX.FLU-FXT.FLU, levels=design)
FINTEXF<-(glmLRT(fit, contrast=mycontrast[,"FINF.TEXF"]))
summary(Y<-decideTestsDGE(FINTEXF, p=0.1)) # (-98,+480)
ttFINTEXF<-topTags(FINTEXF, n=sum(98+480))
sigFINTEXF<-ttFINTEXF[abs(ttFINTEXF$table$logFC) >=1.0,]
nrow(sigFINTEXF)
519
ED<-DGEList(counts=countdata, group=group)
Y<-calcNormFactors(ED)
design<-model.matrix(~0+group)
colnames(design)<-levels(group)
Y<-estimateGLMCommonDisp(Y, verbose=TRUE)
Y<-estimateGLMTrendedDisp(Y, design)
Y<-estimateGLMTagwiseDisp(Y, design)
fit<-glmFit(Y, design)
mycontrast<-makeContrasts(FINF.TEXF=FIN.FLU-TEX.FLU, FINF.FXTF=FIN.FLU-FXT.FLU, TEXF.FXTF=TEX.FLU-FXT.FLU, levels=design)
FINTEXF<-(glmLRT(fit, contrast=mycontrast[,"FINF.TEXF"]))
summary(Y<-decideTestsDGE(FINTEXF, p=0.1)) # (-98,+480)
ttFINTEXF<-topTags(FINTEXF, n=sum(98+480))
sigFINTEXF<-ttFINTEXF[abs(ttFINTEXF$table$logFC) >=1.0,]
nrow(sigFINTEXF)
519
Thank you very much!
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