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jvelotta 04-09-2013 06:39 AM

RNA Seq: differential gene expression with multiple factors

I'm looking to assess differential gene expression using Illumina HiSeq reads. I have a two-factor experimental design (three divergent fish populations each treated at two salinities). I would like to assess differential expression using a two-way model - specifically I want to pinpoint genes for which there are significant interaction effects.

Does anyone know if any of the (many) RNA seq tools available can run a model of this kind (probably a generalized linear model) using these data?

Thanks so much.

kopi-o 04-09-2013 08:57 AM

edgeR and DESeq/DESeq2 can do this and yes, they use GLMs. There are probably other packages too but these are the ones that come to mind.

jvelotta 04-09-2013 11:37 AM

Thanks. Any experience with either of these packages? Are there major differences?

kopi-o 04-09-2013 11:55 AM

I'm a satisfied user of both. I would not say there are major differences between them.

shi 04-09-2013 02:48 PM

Another option is limma. You use its lately developed 'voom' function to normalize your data and then you can analyse your data in the same way as analyzing microarray data.

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