Quote:
Originally Posted by younko
Hello chadn737
I also have similar problems.
I do not have a replicate. but I have several patients having same disease.
For example, in my case, I have 10 patients having same disease.
We treated the drug and did RNAseq for beforedrug/afterdrug.
What we want to do is to find the differentially expressed genes reponsing to the drug. Instead of replications, we have 10 patients samples.. for pre/post.
I used edgeR and DESeq for this.. but I could not find the any DEG with adjusted p value .. So I am thinking to look at the p value instead of adjusted pvalue by considering the fact that we can have FP... of course...
Would it be okay?

As mikep said, your biological variation between patients is likely the problem, obscuring your treatment affect.
You could try simple pairwise, patient by patient, comparisons using some of the available nonparametric methods, like a Rank Product analysis (RANKPROD in R, for example uses permutation tests in the absence of replicates), the R tool GFOLD (which uses bayesion posterior prediction of fold change to calculate pvalues and does not require replicates).