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Old 07-18-2014, 06:50 AM   #84
bigmw
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Join Date: Aug 2013
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Obviously, no pathways has q-val <0.1. this is still common due to the sample size, noise level etc in your data. You may do either one or both of the following:
-increase the q-val cutoff, something like:
q.cut=0.2
sel<- fc.kegg.p$greater[,"q.val"] < q.cut & !is.na(fc.kegg.p$greater[,"q.val"])
sel.l<- fc.kegg.p$less[,"q.val"] < q.cut & !is.na(fc.kegg.p$greater[,"q.val"])

-use the native GAGE workflow instead of the joint workflow. The former has higher testing power as it take sample size into account. For details check my answer at #81 of this thread above.

I assume your data and analysis was done correctly above. But first of all, make sure you did not mix up your control and experiment samples (or their labels), and also your data quality has no major problem.



Quote:
Originally Posted by crazyhottommy View Post
I did try using all the genes, but still no pathways are selected....Maybe that's just the nature of my data?
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