Voom transformation of RNA seq raw counts data

I have RNA seq data of raw gene counts that I want to transform for linear modelling. I am trying to voom transform, to do a weighted analysis.

Data frame: prac_count_10

gene         S1     S2    S3   S4    S5
ENG0000456   0      1     10   145   24
ENG0000458   7      2     9    0     0
ENG0000657   76     12    56   10    2
ENG0000689   0      0     0    3     5



Code:

prac_prac_10 <- voom(prac_count_10[,2:5], design=NULL, lib.size=NULL,
normalize.method = "none", span = 0.5



However this doesn't give an output with the gene sample names and logCPM values. Would like an output with gene id's and logCPM values for linear modelling.

Also tried:

cpm <- cpm(prac_count_10)
lcpm <- cpm(prac_count_10, log=TRUE)

$$$$


Try to use DElist() function before you transform, and also make rownames first.

counts <- prac_count_10[,-1]

rownames(counts) <- prac_count_10[,1]

DGE1 <- DGEList(counts)


And then continue with your voom...

• Thank you. what package is DElist in? Apr 9 '19 at 8:21
• That would be edgeR.
– benn
Apr 9 '19 at 8:23
• If I do: prac_count <- data.frame(prac_count, row.names=1), counts<- prac_count[,1], rownames(counts) <- prac_count[,1], DGE1 <-DGEList(counts)  If doesn't work... have I missed a step? Thank you so much Apr 9 '19 at 8:31
• That's not the code I gave in my answer, is it?
– benn
Apr 9 '19 at 8:48
• Okay, thank you for your kind help Apr 9 '19 at 10:37