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Replies
Comment: Per gene Covariates
by
Michael Love
34k
If you have per gene and per sample corrections, you can use normalization factors (see DESeq2 paper and vignette first on this topic).
Fo…
Comment: deseq2 machine sizing best practices for very large data set
by
Michael Love
34k
I recommend and use limma-voom for large bulk datasets often, it is much faster than GLM-based methods.
Comment: branchpointer: trouble to read gtf
by
b.signal
•
0
Hi Frank,
Your example gtf is missing a gene_id. In the old code we also required a transcript_type/transcript_biotype, and a gene_type/g…
Comment: deseq2 machine sizing best practices for very large data set
by
ATpoint
▴
840
https://support.bioconductor.org/p/73399/#73400
Comment: Per gene Covariates
by
Paola
•
0
Hi Michael,
I have a similar problem where we want to run a LRT analysis on RNA-Seq to find differences across 4 groups and correcting for…
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