Go Visualization From A Set Of Peaks And Set Of Ontology Result Files
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12.0 years ago

Hola!

A naive question(set of questions), how to proceed with the plotting of GO enrichment analysis from a list of peaks. There is lot of information available on the web and to me most of it is confusing. I have a list of significant binding sites such as peaks from the Macs peak caller. I used Homer analysis tool for GO enrichment and got few files namely biologicalprocess.txt, cellularcomponent.txt, molecular_function etc. How to plot these data tables in terms of bar charts or may be the more complex tools like Gelphi.

After taking the top 17-18 hits from the Biological Process file, I generated a plot something like enter image description here But if you see some terms like positive regulation of cellular process & regulation of cellular process seems to be under one category. How to deal with this, manually or there is automated system(should be). How GoSlims are different to these. Can one convert this to GoSlims and how to proceed with that.

Thanks

P.S. ReviGo is nice tool, just checked.

chip-seq go gene-ontology • 4.8k views
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Entering edit mode
12.0 years ago

I'm not quite sure what you are trying to achieve, but possibly you would like to categorize your GO terms in terms of of enrichment, taking into account the hierarchical structure of the GO tree.

If this is the case, have you looked at topGO from Bioconductor? You will need to prepare your data acccordingly (all genes from your genome, GO terms for all these genes, and selected genes of interest) and play around with the different algorithms available to analyse the GO tree in terms of enrichment. You can have a look at this post if you are struggling with preparing your data and don't understand the topGO guide.

The topGO paper explains in detail the algorithms: http://bioinformatics.oxfordjournals.org/content/22/13/1600.abstract

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Leonor, I will look at it. Thanks

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12.0 years ago
Sudeep ★ 1.7k

along the lines of topGO I would also suggest looking at BiNGO, Cytoscape plugin.

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