Question: normalized rna seq data
0
gravatar for maryak
14 months ago by
maryak20
maryak20 wrote:

My TMM normalized RNA seq data has some positive values ,zero values and non zero values .Now what does these three types of values indicates?how i will know that a gene is expressed or not or differently expressed?

rna-seq gene • 551 views
ADD COMMENTlink written 14 months ago by maryak20
1

Please describe in more detail what you did. Also, read carefully the edgeR User Guide and DESeq2 vignette, they have plenty of information on how to perform differential expression analysis.

My TMM normalized RNA seq data has some positive values ,zero values and non zero values

Positive values are non-zero. What you shouldn't see is negative values. All values are corrected counts of reads mapping to genes.

ADD REPLYlink written 14 months ago by h.mon29k

i have negative values as well.Can you please guide me what might went wrong?

ADD REPLYlink written 14 months ago by maryak20

Perhaps you should share then what you did?

ADD REPLYlink written 14 months ago by WouterDeCoster42k
    library(edgeR)
    RNAseq2 <-read.delim("C:\\Users\\hp \\Desktop\\BRCA.tsv",header = TRUE)
    rnames <-RNAseq2[,1]
    MA <- data.matrix(RNAseq2[,2:49])
    MAA  <- (2^MA)-1
   dge <- DGEList(MAA)
    dim(dge)
    #getCounts(dge)
    cal <- calcNormFactors(dge,method = "TMM")
    RR <- cpm(cal,normalized.lib.sizes=TRUE ,log = TRUE,prior.count = 1)
    hist(RR)
    row.names(RR)<- rnames
    #head(RR)
    write.table(RR,"C:\\Users\\hp folio\\Desktop\\TMM3.tsv",sep='\t',row.names=TRUE,col.names = TRUE)
ADD REPLYlink modified 14 months ago • written 14 months ago by maryak20
1

edgeR expects raw counts as input, not transformed data. You should do:

dge <- DGEList( data.matrix(RNAseq2[,2:49]) )
ADD REPLYlink modified 14 months ago • written 14 months ago by h.mon29k

Actually my raw count data was log 2 transformed so i reversed the transformation in order to get original counts

ADD REPLYlink written 14 months ago by maryak20
1

It would be much better if you can get access to the original data without having to tamper with it like this.

ADD REPLYlink written 14 months ago by WouterDeCoster42k
1

You do not actually do that... you return it to the linear scale and then subtract 1

MAA  <- (2^MA)-1

If your input data is log2-transformed, then you just need to do:

MAA  <- 2^MA

This may explain the negative counts

ADD REPLYlink written 14 months ago by Kevin Blighe53k

sorry i missed to mention that the data is log2(count+1) transformed... so that why i did

MAA  <- (2^MA)-1

but still unable to figure out wheres the problem

ADD REPLYlink written 14 months ago by maryak20

agree with WouterDeCoster here. Moreover, why would you do that (= the log2 transformation)?

ADD REPLYlink written 14 months ago by lieven.sterck6.7k
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