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Old 06-22-2012, 04:51 PM   #41
vyellapa
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If I am trying to find differentially expressed genes between say tumor and relapse samples and I have 3 samples each for tumor and relapse patients. Can I group 3 tumor patients as replicates and do the same for relapse samples to get the differentially expressed genes between tumor and relapse cases?

Would such grouping cause any weird results to inaccurate variance estimation that would result from 1)biological noise 2) between sample variation
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Old 06-24-2012, 02:39 AM   #42
Simon Anders
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Sure, it is correct to group in this manner. Of course, you will not get any results due to the high between-group variance, but I guess you know that there is no chance of finding differences between tumour types with so few samples.
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Old 07-15-2014, 03:07 PM   #43
BFM
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Hi i am using DEseq with no replicates

> conds <- factor( c( "A-Mock", "A-Infect", "B-Mock", "B-infect" ) )

i need to compare the diff expression between A-mock and A infect similarly B mock B infected. It doesnt seem to work i am using

res <- nbinomTest( cds, "A-mock", "A-infect", )
> res <- nbinomTest( cds, "B-mock", "B-infect", )

but at the end i am getting only one p value. How to solve this problem. Please help
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Old 07-15-2014, 07:38 PM   #44
Jeremy
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Those are two different tests, but you are overwriting the first reslt object (res) with the second.

res <- nbinomTest( cds, "A-mock", "A-infect", )
res <- nbinomTest( cds, "B-mock", "B-infect", ) # replaces the above result with the new one

Call one resA and the other resB for example. In the end you might want to merge the two for comparison or just write out both as separate tables.

resA <- nbinomTest( cds, "A-mock", "A-infect", )
resB <- nbinomTest( cds, "B-mock", "B-infect", )
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