15 days ago
FWNL15
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4 weeks ago • updated 18 days ago
Jinyue
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9 weeks ago
FWNL15
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7 months ago
sissialva21
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坤
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written 5.6 years ago by
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updated 12 months ago by
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Lin
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updated 2.2 years ago by
Yuan Tian
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written 2.3 years ago by
learning.iq84
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sinha.puja
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3.0 years ago
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updated 3.0 years ago by
Yuan Tian
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written 3.1 years ago by
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3.1 years ago
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3.3 years ago
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Recent ...
Replies
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…
Comment: deseq2 machine sizing best practices for very large data set
by
aedavids
•
0
Hi Michael
These are bulk samples.
I like your idea of running a couple of subsets to get a rough idea about the required resources. I am…
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