Hi Everyone,
I am using DEseq package for my RNA SEQ samples so as to find differentially expressed genes between 2 samples
I have 2 RNA seq samples. One of them is CONTROL and the other sample is prepared by UV irradiation. Lets call the other sample as X.
Now since I don't have biological replicates in my case, I will have to use DEseq PACKAGE (working without any replicates section).
I randomly gave 2 conditions, "control" and "x" to my sample and I am looking for differentially expressed genes between 2 samples(up regulated or down regulated).
After following all the steps of DEseq at the last step where final results are to be computed
res <- nbinomTest(data,"control","x")
In the final output padj is always 1
padj - p-value adjusted for multiple testing using Benjamini-Hochberg to estimate the false discovery rate
Should I take into account only the pval column in my case or is there any other way to analyze this situation where I want to find differentially expressed genes between 2 samples(without biological replicates).
Regards
Varun
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written
by
Varun Gupta
Its difficult to know statistical significance (eg. p-value) of differences in expression when you don't have replicates.
One thing you can do to maybe get some meaning out of the data is sort your genes by the unadjusted p-value, or by fold-change, and look at the top/bottom genes. You can also feed this sorted list to GSEA to check for gene-set enrichment.
Well that is what I am doing now to analyze top/bottom genes by fold-change. Also are you talking about GSEA R PACKAGE called as GSEABase?? Tell me about it and I will try it. Thanks
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written
by
Varun Gupta
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