Fisher exact test
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@elhamdallalbashi-11418
Last seen 7.2 years ago

Hello everyone,

I have some human RNA-seq data (control/treatment), I did differential expression analysis (with CLC Genomics) and now I want to calculate p-value by fisher exact test.

 

I read “Gen set testing” pdf, but I cannot understand with what parameter I should fill a 2x2 contigency table?

 

In addition to, I have 28031 genes (there are lncRNA), I should organize table for each gene?

rnaseq differential gene expression • 2.8k views
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If you want help, you need to clearly state what you are trying to do. Just naming a statistical test doesn't tell anybody what your goals are, and I doubt anybody knows what the 'Gen set testing' pdf might be. You will get better luck with answers if you take the time to ask clear questions that others can understand without having to infer what you might be getting at.

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Dear James W.MacDonald

I have some experiment (effecting some drugs on some cancers) for study on LncRNA,for Enrichment of the gene sets for ID genes ( given a set of genes that are up-regulated or down regulate under drug conditions) I want to calculate p-value by fisher exact test. 

I read the article of (Identification of long non-coding RNAs involved in neuronal development and intellectual disability) which calculate p-value by fisher exact test for Enrichment of the gene sets for ID genes of lncRNA.

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davide risso ▴ 950
@davide-risso-5075
Last seen 13 days ago
University of Padova

The way you populate the 2x2 table is, for some definition of differential expression (DE):

DE genes in set         |  non DE genes in set

----------------------- | ----------------------

DE genes not in set     | non DE genes not in set

You can then use the `fisher.test` function to obtain the p-value. Obviously, you will have one table per gene set and hence a p-value per gene set, iterating through the list of gene sets.

That said, there are better methods to perform geneset enrichment analysis in RNA-seq, including some implemented in limma, see the test case in Chapter 18 in the limma user's guide, available here:

https://www.bioconductor.org/packages/devel/bioc/vignettes/limma/inst/doc/usersguide.pdf

Obviously, there are many alternatives to these tests, and many more Bioconductor packages that can do the job: the BiocViews "GeneSetEnrichment" returns 69 packages, and it's a good place to start.

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