Best software for differential gene expression analysis?
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7.5 years ago
StephanieK ▴ 110

Hi all, I have gene expressions data sets from three species (human, rat and mouse). Each data set either has two groups of individuals (i.e. young and old) or multiple groups (i.e. multiple ages). I want to find which genes are differentially expressed with age.

I'm new to the field and I've done some reading, but I'm wondering do researchers think that the best software to do this analysis (i.e. identify differentially expressed genes between two groups or between multiple groups) would be the EDGE package in R?

I'm looking for a software: 1. Where I feed the software groups of samples and it will give me back the genes over/underexpressed between the groups. 2. I have a lot of data sets, so looking for something in unix, R or python. 3. Must not be specific to any one organism, as I don't want to have to run a separate software for human, mouse and rat. 4. Not be buggy or over-complicated, and if possible, be widely used, No doubt I'll run into problems, so it would be great to have somewhere to ask for help.

Would EDGE be a suitable package for this type of analysis? What other software packages are groups using?

Thanks

Edit: I should clarify that I am only dealing with Affymetrix data, no RNASeq data.

expression edge limma R gene • 5.6k views
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In OPs defense, both threads are rather old. Obviously things have changed since these discussions.

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It's not RNA-seq but microarray.

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7.5 years ago

I think the most up to date workflow will be the one from Bioconductor, that's R.

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Deleted my answer, did not realize affymetrix until too late - thanks for that :)

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I use limma for the random array data I still have to deal with.

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