Hi, I am trying to calculate statistics for my proteomic data using LIMMA package so I can create some volcano plots. I have normalized log2 transformed intensities with imputed NA values for 2 samples each with 3 biological replicates so 6 columns (+1 annotations). When using LIMMA for some reason several proteins have identical adj.P.Val even tho P.Value is different and logFC and AveExpr is correct and P values seem fine to me. It looks terrible when I use adj.P.Val for volcano plots as several dots are in one line with several lines like that. This happens also with different data and there are several groups like this among whole LIMMA calculated sheet:
ID logFC P.Value adj.P.Val GAA -0,002 0,993 0,997 TUBB2B -0,005 0,988 0,993 KIF5B -0,002 0,984 0,993 BPIFB1 0,013 0,986 0,993 ARPC1B -0,003 0,984 0,993 TXNDC5 0,003 0,985 0,993 KLC4 -0,001 0,989 0,993 ...
adj.P.Val are identical even if all decimal places are used...here I just used fewer of them to make it clear
This is my code:
#data loaded to my_data as.matrix with specified rownames and colnames design <- model.matrix(~gl(2,3)) Limma <-topTable(eBayes(lmFit(my_data, design)), sort.by = "none", number = 1000,adjust.method="BH")
Any idea what is wrong? As I suppose it should be very unlikely to have identical adj.P.Val for different proteins with different values.