Replicate for DESeq2
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@sushant-pawar-9287
Last seen 5.4 years ago
Nashik

Hi all ,

I am running DESeq2 for Transcriptome analysis , Sometimes it is not possible to make replicate for each sample because it increases cost of analysis .So is it all right to simulate the replicate for case and control samples.

for e.g

- untreated (original counts of control)                                         - treated (original counts of case) 

- untreated*0.9                                                                             - treated*0.9

- untreated*1.1                                                                             - treated*1.1

Or suggest me some better idea , so it is helpful for our statistical analysis.

 

deseq2 • 1.2k views
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If you don't have replicates, you can't do statistics. DESeq2 is designed for gene level counts, not transcript level, just to make that clear. Michael Love will probably comment with more detail on how DESeq2 works without replicates, but I don't think multiplying your gene counts by a constant will be useful. 

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@mikelove
Last seen 1 day ago
United States

No, definitely do not add fake data. This will give highly misleading results with many false positives.

The DESeq function does provide some conservative, exploratory results if you plug in data without replicates. Please read the help page for ?DESeq.

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@sushant-pawar-9287
Last seen 5.4 years ago
Nashik

Thank you guys ,

This is really helpful for me.

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@sushant-pawar-9287
Last seen 5.4 years ago
Nashik

I have used this syntax for without Replicate by changing only sampleCondition command in DESeq2 .

so, is it all wright

 ==========================================================
library(DESeq2)
directory<-"/home/dgl/110_AmpliseqRNA/all_samples_with-replicates/1790_Cervical-Liver_with_LN_R2"
sampleFiles <- grep("treated",list.files(directory),value=TRUE)
sampleCondition<-c("treated","untreated")
sampleTable<-data.frame(sampleName=sampleFiles, fileName=sampleFiles, condition=sampleCondition)
sampleTable
ddsHTSeq<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~condition)
colData(ddsHTSeq)$condition<-factor(colData(ddsHTSeq)$condition, levels=c("untreated","treated"))
dds<-DESeq(ddsHTSeq,fitType="mean")
res<-results(dds)
res<-res[order(res$padj),]
head(res)

mcols(res,use.names=TRUE)
write.csv(as.data.frame(res),file="Raw_File_deseq2.csv")

FileforIpathway=res[,c(2,6)]
write.csv(as.data.frame(FileforIpathway),file="File_for_iPathway_deseq2.csv")

pdf("DEseq2_MA_plot.pdf")
plotMA(dds,ylim=c(-10,10),main="DESeq2")
dev.off()

pdf("DESeq2_Dispersion_plot.pdf")
plotDispEsts(dds)
dev.off()

=======================================================================

 

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