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how to use log transformation with read count data?

Hi All,

I have a data set ~20000 observations, and when I plot the histogram for this data,I found it skewed to the right. I used log transformation, but I got infinity values because I have many values equal to zero. Is there any way to use the log transformation without removing these zero values because it's important in my analysis. Or is there any other to transformation this data.

r
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updated by Ram Ram • written by M K M K

We add 1 to RNA-seq counts for all the transcripts before the log transformation to get rid of the negative values.

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updated by Ram Ram • written by Ashutosh Pandey Ashutosh Pandey

so this will not effect the results at all.

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updated by Ram Ram • written by M K M K

2 answers

You should use the regularized log or the Variance stabilizing transformation. The two transformation are imlpement in DESeq2 package. Check the vignette, it's very well made : http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html

rld <- rlog(dds)
vsd <- varianceStabilizingTransformation(dds)

where dds is a DESeq2 object. You can input data from a count matrix or htseq output (again check the vignette)

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updated by Ram Ram • written by Nicolas Rosewick Nicolas Rosewick

When I try rlog or varianceStabilizingTransformation I get the following error:

Error in DESeqDataSet(se, design = design, ignoreRank) : 
  some values in assay are not integers

my input data is RNA Seq count data (a matrix) where some values are 0 and rest are positive integers. Can you guide me why I am getting this error ? Thanks

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updated by Ram Ram • written by Bioinformatist Newbie Bioinformatist Newbie

could you post the different commands you used please?

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updated by Ram Ram • written by Nicolas Rosewick Nicolas Rosewick

I'd suggest using a pseudocount. Maybe a value of 0.0001 added to the actual values would make very little diff in log transformation.

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written by Ram Ram

do you mean by adding small value to the log transformation like the example below

data<- read.table(.........)
tran_data<- log(data+0.0001)
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updated by Ram Ram • written by M K M K 
tran_data<- log2(data+1)

because log2(1) is zero.

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updated by Ram Ram • written by Chirag Nepal Chirag Nepal

I think 1 is a better (and more common) number to add. the log of 0.0001 is -9 so probably not what you want for you zero counts

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updated by Ram Ram • written by brentp brentp

I should've thought of that. I agree, 1 is much better!

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written by Ram Ram

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