A multipart question.
I have exracted log2 transformed normalized TCGA expression data for ~10 genes of my interest. How can I determine wether the genes are differentially regulated between the subtypes of cancer?
1) I think Anova/Kruskal wallis + post hoc for each gene followed by FDR adjustment be ok? As bayesian methods (limma) which borrow info across genes might not well suited for this small number of genes?
2) Furthermore, in genetics filed, and in studies with 2-4 genes, I have hardly seen p value adjustments, which affects decision about borderline p values. Shall I stick to this practice (I mean is there a scientific reason behind it?)
3) not searched for this on biostars so you may skip this: Yet another question, how is the Number of tests for anova+ post hoc determined to determine adjusted p vals?