TMM normalization of cancer RNA seq
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marak • 0
@marak-18210
Last seen 5.4 years ago

i have RNA seq counts data when i apply TMM normalization why do i also get negative values beside positive one my source code is below:

 

library(edgeR)
RNAseq2 <-read.delim("C:\\Users\\hp folio\\Desktop\\BRCA.tsv",header = TRUE)
rnames <-RNAseq2[,1]

MA <- data.matrix(RNAseq2[,2:60])
MAA  <- (2^MA)- 1
head(MAA)
dge <- DGEList(MAA)
dim(dge)
cal <- calcNormFactors(dge,method = "TMM")
RR <- cpm(cal,normalized.lib.sizes=TRUE ,log = TRUE,prior.count = 1)
hist(RR)
row.names(RR)<- rnames
write.table(RR,"C:\\Users\\hp folio\\Desktop\\TMM3.tsv",sep='\t',row.names=TRUE,col.names = TRUE)

 

 

pls:my data was log2(count+1) transformed so i have also reversed the transformation.i will be very thankful if anyone help me.

 

cancer normalization • 1.0k views
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@steve-lianoglou-2771
Last seen 14 months ago
United States

You are getting negative values because you are calling cpm(...) with log = TRUE.

Some of your raw/unlogged counts-per-million values are falling between 0 and 1, and therefore their log2 values are negative.

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thanks a lot . i removed log=true and it worked.Can you please guide me that histogram of TMM normalized values must be in normal distribution form?

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Entering edit mode

There is no reason to expect that the logCPM values would be normally distributed. Why do you think that they should? And do note that many normal distributions include negative values (for example the standard normal distribution), so if you were expecting your 'normalized' data to be normally distributed it shouldn't have bothered you that some values were negative.

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