Differential analysis on gene expression data

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.

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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.

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?

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 ‚Äúdifferential abundance‚ÄĚ because it can be applied more generally than RNA-seq but it looks pretty good to me:

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