I have RNA-Seq data with paired design, each tissue with treatment and untreated data. I have used DESeq2, using
normTransform(), to calculate the pairwise fold-changes. So Initially I have 60 samples and now I have a Fold change matrix of 30 columns and for all genes.
GeneID sample1_T sample1_U sample2_T sample2_U . . . sample30_U gene1 n n n n . . . gene2 n n n n . . .
GeneID sample1 sample2 . . . . sample30 gene1 -3.11 -1.3 . . . . -0.5 gene2 3.12 1.12 . . . . 0.5
Now I would like to filter the data such that the genes which are consistently up/down-regulated in at least 80% of the samples or 60% of the samples, genes that does not have any consistent up/down regulation etc.
I would like to calculate a statistical score which represents the number of samples the gene shown to be up/down regulated and extent of fold change, such that I can use that score to filter the matrix.
I did a DE analysis using the paired-design and tried to use the adj-Pvalue for filtering the data, but I do not know (Edit) if I can use this to filter as per my criterial.