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looking for an R package for GO term analysis
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10 months ago
Javad • 60

Hello,

Can anyone suggest a simple R package to perform GO term analysis. Specially I am looking for a package that can produces publication quality figures and heatmaps regarding GO term results.

Thanks in advance

RNA-Seq next-gen • 9.9k views
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10 months ago
Republic of Ireland

There are quite a few packages out there, and there was a thread on this already: GO enrichment analysis using R

See also my answer to this thread on GO term reliability: A: Go annotation reliability ?

One that is not mentioned in these threads is topGO

Another one with heatmaps is GOexpress

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Thank you very much for your response. Because I am new to this area, I would like to know a little bit about how GO term analysis works. There are few publications available but most of them are highly technical and hard to understand. Is there a good paper about it that explains the idea behind GO term analysis for a beginner?

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Well, you basically have to be very careful with 'gene enrichment', as I would call it in the broadest form ('gene enrichment' includes 'GO analysis'). How it works is that each enrichment term has a number of genes associated with it.

For example:

DNA double strand break repair = TP53, ATM, BRCA1, BRCA2, etc.

If we then have data that shows that 3 of these genes are down regulated, then we can have high confidence that our DNA double strand break repair pathway is going to be adversely affected.

The number of genes assigned per term is key, and also the level of evidence behind each term:gene association. That's why I pasted the link to the other thread where I explain the evidence codes behind the GO terms: A: Go annotation reliability ?

This is just me explaining it at the fundamental level.

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20 months ago
Diwan • 560
United States

Check bioc package "clusterprofiler". https://guangchuangyu.github.io/2016/01/go-analysis-using-clusterprofiler/

For heatmaps of GO enrichment, check "revigo". They provide the output as R script which you can load in R and manipulate colors etc. to suit your need.

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