Question: Transforming RNA-seq data- (tpms) - what is the best practice for dealing with zeros for the purpose of deconvolution?
gravatar for nancy
13 months ago by
nancy70 wrote:

Using Cibersort to deconvolve bulk RNA-seq data to specific cell-types based on expression values from bulk RNA-seq. I have a series of samples, and their individual TPMs as computed by Stringtie. Each column is a sample, each row is a gene. Since cibersort only accepts non-zero values, I am trying to understand the best way to transform those tpms which = 0.

Are any of the below more preferred/accurate?

  1. Treat all samples and all rows the same- Add a small (0.0001) value to all the rows for all samples
  2. Treat all samples the same for those rows which = 0 - Add a small (0.0001) value to only those rows with 0
  3. Treat each sample differently - Find the smallest non-zero value for each sample, and add that value toall the rows for that sample.


ADD COMMENTlink written 13 months ago by nancy70

What do the authors of Cibersort do in their paper?

ADD REPLYlink written 13 months ago by kristoffer.vittingseerup3.0k
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