Hi Ryan, Thanks for taking out time to reply to my question. I have samples from two tissues - Heart (20 different developmental stages) and Control (rest of the body, single fused sample from multiple time points). I performed 'limma' analysis (GLM approach) to identify up-regulated genes for each of the Heart stages (n=20). Ex comparisons: Heart Stage-1 vs. Control-X Heart Stage-2 vs. Control-X ..... Heart Stage-20 vs. Control-X Now I would like to rank genes on the basis of their enrichment in heart across all stages. So that a gene which is highly enriched in heart should rank high (on top) and genes which are not enriched in heart should rank low (at bottom). Is there any way to combine 't-stats' for each stage to a single metric? Or any other method rank genes that are enriched in Heart across all stages? Actually I do have F-statistic. But I think that F-stat is high for gene which shows variable enrichment i..e gene which is not enriched in 5 stages but enriched in 15 stages will have better F-stat reather than a gene with enrichment in all 20 stages. Therefore 'F-stat' doesn't seem to be the correct indication of enrichment level across all stages. I might be wrong, please correct me if that the case. Best AK On 08/28/2014 06:09 PM, Ryan C. Thompson wrote: > Hi Atul, > > Typically if you are testing multiple contrasts simultaneously, you > would use an ANOVA test that would five you an F statistics (and > corresponding p-value). But it's not exactly clear if that's what > you're asking for, Can you explain in more detail exactly which > hypothesis you are trying to test? Ar you trying to test whether any > of the Stages is different from the control, or are you trying to test > whether genes are changing between all Stages? > > -Ryan > > On Thu 28 Aug 2014 12:52:47 PM PDT, Atul wrote: >> Hi All, >> >> I was wondering whether there is any approach to combine 't-stat' from >> different comparisons but using same control. These are my contrasts: >> >> Stage1 vs ControlX >> Stage2 vs ControlX >> Stage3 vs. ControlX >> ......... >> Stage 20 vs. ControlX >> >> Here the control is same i.e. same sample for all contrasts. From >> 'limma' analysis I have Fold change, t-stats and p-values for each gene. >> >> Now, is it possible to combine 't-stats' from all different stages to >> single value? Or compute a single combined value for all the contrasts. >> So, that this single metric could be used to rank genes across all time >> points. Is there any package available to do so? I can find methods to >> combine p-values but not the 't-stat'. >> >> Thanks >> >> AK >> >> >> >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> 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 [[alternative HTML version deleted]]