Hi, Is it possible to have a single protocol to analyze differential gene expression for experiments of different design? A dataset like GDS3715 in GEO, for example, has both levels and sub-levels (agents). One of the levels, say insulin resistant, is divided into sub-levels treated and untreated samples. GDS162 on the other hand is grouped into just two levels(no sub-levels). Running res = sam(gdseset, gdseset$disease.state)works fine for data with just levels. res = sam(gdseset, gdseset$agent) understandably groups everything into 2 classes, treated and untreated, which doesn't make much sense, to me anyway. And using res = sam(gdseset, gdseset$disease.state$agent) doesn't work. Is there a way to possibly identify, correctly assign and pair up such sub-level data if and when the script comes across it? Thanks. -Avoks

Hi, Avoks. This is something that could be accomplished using a linear modeling framework, so limma might be a good tool to use. However, automatically determining the experimental design may be difficult. I do not know of an automated system for analyzing datasets of arbitrary complexity that does not require human intervention. Sean On Wed, Sep 14, 2011 at 12:03 AM, Avoks AO <ovokeraye at="" gmail.com=""> wrote: > Hi, > > Is it possible to have a single protocol to analyze differential gene > expression for experiments of different design? A dataset like GDS3715 > in GEO, for example, has both levels and sub-levels (agents). ?One of > the levels, say insulin resistant, is divided into sub-levels treated > and untreated samples. GDS162 on the other hand is grouped into just > two levels(no sub-levels). Running res = sam(gdseset, > gdseset$disease.state)works fine for data with just levels. ?res = > sam(gdseset, gdseset$agent) understandably groups everything into 2 > classes, treated and untreated, which doesn't make much sense, to me > anyway. And using res = sam(gdseset, gdseset$disease.state$agent) > doesn't work. Is there a way to possibly identify, correctly assign > and pair up such sub-level data if and when the script comes across > it? > > Thanks. > > -Avoks > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >