Differential analysis on gene expression data

Q&A
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1

Hi
I am wondering if there is any pipeline for differential analysis on log2(TPM+1) data? Can I simplify use limma or other R package recommended?

Thanks ahead for your comments.

1 Like
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Hello - I like to use voom-limma for RNA-seq analysis, but I would recommend instead of using log2(TPM+1) data that use the read count data (also available for download), and follow standard practices/workflow of doing library normalization etc.

3

Hi dllahr,

Thanks for quick response, but do you have more detailed workflow for differential analysis begin with the read count data?
As far as I googled, we can download ExpectedCountProfile, AllGenesEffectiveLengthProfile, and AllGenesTPMLogp1Profile, and import these three matrix to package tximport for DESeq2 analysis. is it right?

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We have our own internal pipeline (not published unfortunately) but these days I tend to check next flow / nf-core for great starting points for standard pipelines and analyses. The one for differential gene expression is called “differential abundance” because it can be applied more generally than RNA-seq but it looks pretty good to me:

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That is so nice of you, Dave. Much appreciated for you kindly sharing.