During the p.adj , many measurements (different genes) from the same sample (i.e one column of the image) does it take all the p values from across all the samples and rank them? or ranking gene by gene and calculate the p.adj?
For example, if we have 100 genes that we want to test for differences between three samples A, B and C, then do we generate 100 p-values for A x B, 100 p-values for A x C and 100 p-values for B x C, for a total of 300 p-values? and adjust all 300 p-values at the same time?
Does that mean all the 300 P-values rank together and do the p adjustment for all the samples (A,B,C) treating as one population?
OR, do we adjust the p-value each sample by sample (column by column)
I have used Bioconductor dep (limma dependent) package for data analysis and for one sample I get p.adj = 1 for all the genes (sample output attached).