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Question: Question regarding best bioconductor package for RNA-seq
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gravatar for Maximilian
8 months ago by
Maximilian10
Maximilian10 wrote:

Dear bioconductor forum,

I have a question: I have to analyse RNA-seq data of different RNA read counts mapped to a human reference genome (already in a matrix) for differentially expressed genes between different samples. I found a paper listing the most recent bioconductor packages for this kind of analysis: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-91.

Because a lot of people in this forum have a lot of experience with this kind of work I wanted to ask if someone please could give me an advice or a tip which bioconductor package would work the best with this task.

Kind regards,

Max 

ADD COMMENTlink modified 8 months ago by b.nota290 • written 8 months ago by Maximilian10
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gravatar for b.nota
8 months ago by
b.nota290
Netherlands
b.nota290 wrote:

For differential expression analysis I always use edgeR or limma (voom or trend).

There are good user's guides available for these packages.

Good luck!

ADD COMMENTlink written 8 months ago by b.nota290
1

Both these are good, as is DESeq2.  When the original poster says "between different samples", we're probably taking that as meaning "between groups of samples"?  Almost all papers we publish, and most we read/review, use one of edgeR, DESeq2 or limma+voom for standard differential gene expression, so they're safe options: if there's a local tradition of using one particular package, go for that, as you'll likely get more support (but Michael Love's support of DESeq2 on here is exemplary, as is Gordon Smyth's on edgeR). If there's anything atypical about your design or hypothesis, then there maybe better alternatives.  

ADD REPLYlink written 8 months ago by Gavin Kelly510

Thanks to both of you for your help!

ADD REPLYlink written 8 months ago by Maximilian10
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