Question: normalized rna seq data
0
gravatar for maryak
4 months ago by
maryak10
maryak10 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 • 294 views
ADD COMMENTlink written 4 months ago by maryak10
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 4 months ago by h.mon24k

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

ADD REPLYlink written 4 months ago by maryak10

Perhaps you should share then what you did?

ADD REPLYlink written 4 months ago by WouterDeCoster37k
    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 4 months ago • written 4 months ago by maryak10
1

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

dge <- DGEList( data.matrix(RNAseq2[,2:49]) )
ADD REPLYlink modified 4 months ago • written 4 months ago by h.mon24k

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

ADD REPLYlink written 4 months ago by maryak10
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 4 months ago by WouterDeCoster37k
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 4 months ago by Kevin Blighe39k

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 4 months ago by maryak10

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

ADD REPLYlink written 4 months ago by lieven.sterck4.2k
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