I am trying to apply voom to expected counts from RSEM (I don't have raw counts). My next step is to compute a differential test using limma.
# matrix I am trying to apply voom to has 1 row and 8021 columns: > dim(tmp)  1 8021 # first five columns > tmp[,1:5] SRR1068687 SRR1068788 SRR1068808 SRR1068832 SRR1068855 ENSG00000149294.16 2528.61 756.53 36 158.95 1652.77 # no NAs in the data > which(is.na(tmp)) integer(0) # this is my design. shows that I have replicates. > rbind(head(design),tail(design)) studyGTEx studyTARGET SRR1068687 1 0 SRR1068788 1 0 SRR1068808 1 0 SRR1068832 1 0 SRR1068855 1 0 SRR1068880 1 0 f3b75630.42da.4b66.96c5.94e9a8142261 0 1 f62f350c.f8b5.4715.ace1.387f7e59cb91 0 1 f637ca92.407d.432e.ba08.2bebe05b96f4 0 1 f835cce2.1ed3.4c59.95a2.4bfef161082b 0 1 fb8c3046.eb74.43ff.ae1d.327453221555 0 1 fdee8bef.5ce2.4ca6.b6b9.3423219a1ea4 0 1 # I get an error when I try to apply voom: > voom(tmp, design = design) Error in approxfun(l, rule = 2) : need at least two non-NA values to interpolate
I searched for the error and I found that it is usually encountered when you have no replicates. However in my case I have enough replicates - studyGTEx has about 7000 and the remaining are studyTARGET. What could be the problem?
NOTE: I have already tried adding more rows (to make nrow(tmp)>1) and I still get the same error.