Question: Gene Set Enrichment Analysis after DESeq2
4
gravatar for Sreeraj Thamban
18 months ago by
Indian Institute of Science Education and Research
Sreeraj Thamban130 wrote:

Hello Biostars, Can anyone tell me how to prepare input data set for GSEA after Differential Gene Expression Analysis by DESeq2? How will I rank the genes? Should I rank based on log2FC or Adjusted P value? Is there any way to generate a GSEA ready data directly from DESeq2?. I was using topGo for gene ontology enrichment analysis before and recently came across GSEA. Which one is better GO enrichment analysis or GSEA? Even after going through the papers I couldn't find a significant difference between above two.

Thank you

gsea rna-seq deseq2 geneontology • 5.0k views
ADD COMMENTlink modified 5 months ago by enxxx23210 • written 18 months ago by Sreeraj Thamban130
1

I like DESeq2. It would be great to have in the future something like ROAST/CAMERA/GSEA in DESeq2 too!

ADD REPLYlink written 5 months ago by enxxx23210
7
gravatar for Prakash
18 months ago by
Prakash920
India
Prakash920 wrote:

Hi Sreeraj

Genes can be ranked based on fold change and P value and that can be used in GSEA package.

you can use this R code for this purpose.

x <- read.table("DE_genes.txt",sep = "\t",header = T)
head(x)
x$fcsign <- sign(x$log2.fold_change.)
x$logP=-log10(x$p_value)
x$metric= x$logP/x$fcsign
y<-x[,c("Gene", "metric")]
head(y)
write.table(y,file="DE_genes.rnk",quote=F,sep="\t",row.names=F)
ADD COMMENTlink modified 18 months ago • written 18 months ago by Prakash920
2

in this case, what parameter should we input into GSEA?

ADD REPLYlink written 15 months ago by langya40

How would you handle NA values?

ADD REPLYlink written 4 months ago by t-jim20
4
gravatar for Michael Love
18 months ago by
Michael Love1.8k
United States
Michael Love1.8k wrote:

Here's a link to an answer I wrote a few years ago for using the gene set testing package goseq following DESeq2:

https://support.bioconductor.org/p/64811/#64815

I'm not sure what kind of input GSEA takes. I also like the methods behind ROAST and CAMERA from the limma package, but I haven't yet worked on integrating with those methods. For those two, you would need to run a limma analysis upstream.

ADD COMMENTlink written 18 months ago by Michael Love1.8k
1

Hey I noticed in the newest DESeq2 version, the default setting of fold change is not shrunken fold change, may I ask why? i thought the shrunken fold change gives you higher confidence.

ADD REPLYlink written 12 months ago by langya40
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