GOStats - HyperGTest - expert opinion needed about the approach selecting gene list
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@srinivas-iyyer-939
Last seen 9.7 years ago
Dear all, I am analyzing gene diff. expression data for a rat chip. instead of asking which biological processes (BP) are enriched for my diff. expressed genes, i am interested in asking which BP are enriched for upregulated genes and which BP are enriched for downregulated genes. For doing this, i seperated the diff. expressed gene lists into two lists (up and down regulated) after filtering the list for p-val 0.001 (this p-val is obtained from a t-test). now I make all up-regulated genes as one 'test list' to see enrichment for BP using entire 'chip'(genes/BP on present on chip) as universe. Similarly, I check enrichement for all downregulated genes keeping chip as universe. My question is: 1. Is it okay to do this way instead of making all up and downregulated genes into a one big list. 2. If i do not see many differential expressed genes, by doing this way, will I be getting all false positive enriched terms. 3. Am I missing any key concept and ending up in a flawed analysis. any suggestions will help me in big way. Thank you ________________________________________________________________ ____________________ Never miss a thing. Make Yahoo your home page.
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@james-w-macdonald-5106
Last seen 10 minutes ago
United States
Hi Srini, I'm not too keen on this idea, mainly because the assumption here is that all up-regulated genes are somehow related and the down-regulated genes are related, but there is no relation between the groups. Let's say that there are 20 genes related to GO term XXX. Half of them are up-regulated, and half are down-regulated (because the first 10 have a negative effect on the expression of the second 10). In this scenario it may be that you won't see any significance for this term, but you might if you didn't separate the two groups. Now this is a pretty stupidly simplistic scenario, which in fact helps prove my point -- for most genes we still have very little information about what processes affect transcription, so making the assumption that genes with positive correlation are related and those with negative correlation are not is a pretty bold assumption indeed. Best, Jim Srinivas Iyyer wrote: > Dear all, > I am analyzing gene diff. expression data for a rat > chip. > > instead of asking which biological processes (BP) are > enriched for my diff. expressed genes, i am interested > in asking which BP are enriched for upregulated genes > and which BP are enriched for downregulated genes. > > For doing this, i seperated the diff. expressed gene > lists into two lists (up and down regulated) after > filtering the list for p-val 0.001 (this p-val is > obtained from a t-test). > > now I make all up-regulated genes as one 'test list' > to see enrichment for BP using entire 'chip'(genes/BP > on present on chip) as universe. > > Similarly, I check enrichement for all downregulated > genes keeping chip as universe. > > My question is: > 1. Is it okay to do this way instead of making all up > and downregulated genes into a one big list. > > 2. If i do not see many differential expressed genes, > by doing this way, will I be getting all false > positive enriched terms. > > 3. Am I missing any key concept and ending up in a > flawed analysis. > > any suggestions will help me in big way. > > Thank you > > > > > > > > > ______________________________________________________________ ______________________ > Never miss a thing. Make Yahoo your home page. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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