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question1:
I have one treated sample and one control sample of RNA-seq readcounts, can I use deseq2 for differential gene expression analysis? (I guess this can not assume the within-condition variation).
question2:
If I have two groups and either of the groups has only one sample(such as[ (A1,A2) (B1)] or [ (A1) (B1,B2)] ), whether it is proper to use deseq2
question3:
Regarding the no replicated situations(both treated and controled no replications; controled no replications; treated no replications), I should choose deseq2 or deseq or edger or limma(voom)?
thanks a lot.
Thanks for your immediate reply,Michael.
I read mannual for several times. In the part 5, there is one point.
5.8 Can I use DESeq2 to analyze a dataset without replicates? If a DESeqDataSet is provided with an experimental design without replicates, a warning is printed, that the samples are treated as replicates for estimation of dispersion. This kind of analysis is only useful for exploring the data, but will not provide the kind of proper statistical inference on differences between groups. Without biological replicates, it is not possible to estimate the biological variability of each gene.
I can not understand
"This kind of analysis is only useful for exploring the data, but will not provide the kind of proper statistical inference on differences between groups."
means.
For (1) you have no idea the degree of within-group variability, so you can't perform statistical inference (determining if the difference you see is more than you would typically see among replicates within one condition).
thanks a lot