[BioC] How to compare GO results

Alex Sanchez asanchez at ub.edu
Wed Aug 19 20:32:08 CEST 2009


Hello

goProfiles works with 'organism' anotation packages ('org.XXX.XXX.db')
There is an Arabidopsis annotation package 'org.At.tair.db' in the next 
version of BioC althoug I'm not sure if this is the one you need.
You will find it in the Bioc-development site.
http://www.bioconductor.org/packages/2.5/data/annotation/html/org.At.tair.db.html

Once you have installed it the use with goProfiles should be 
straightforward.

For instance

library(goProfiles)
library(org.At.tair.db)
tab1 <- toTable(org.At.tairENTREZID)
genes <- sample(tab1[,1],100)
ara.MF.Profiles <-basicProfile(genelist=genes, onto='MF', level=2, 
orgPackage="org.At.tair.db",  empty.cats=FALSE)
print(ara.MF.Profiles)

will yield a basic profile at level 2 of the MF ontology for a random sample 
of 100 Arabidopsis genes

I have tried it with R-2.10.0 but it should work with R-2.9.z

Alex

-----------------------------------------------------------------------------------------------------

Dr. Alex  Sánchez.
Associate professor. Statistics Department. University of Barcelona.
Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain
asanchez_at_ub.edu
Statistics and Bioinformatics Unit
Institut de Recerca. Hospital Universitari Vall 'Hebron
Passeig Vall d'Hebron 112-119. 08034 Barcelona
asanchez_at_ir.vhebron.net
----------------------------------------------------------------------------------------------------






----- Original Message ----- 
From: "Johannes Hanson" <s.j.hanson at uu.nl>
To: "Alex Sanchez" <asanchez at ub.edu>
Sent: Wednesday, August 19, 2009 11:25 AM
Subject: Re: [BioC] How to compare GO results


Thanks, THis software is answering most of the questions I have -
excellent.

However I am working with Arabidopsis data (Affymetrix ATH1 slides).
As far as I understand the annotations files are not availible for
arabidopsis. Is that something that can be solved no or in the future
releases.

Johannes

On 15 Sep 2009, at 10:03, Alex Sanchez wrote:

> Hi Johannes
>
> There are several packages in BioC that you can use to do GO  analysis or 
> to mine GO analysis results.
> You can find most, if not all, of them in the Bioconductor GO task  view. 
> (Curiously topGO is not there).
>
> http://www.bioconductor.org/packages/release/GO.html
>
> I am the maintainer of the 'goProfiles' package which is, in  principle, 
> developed to answer the type of question you pose.
> If you have any questions about its use I'll be pleased to try to  help 
> you at answering them.
>
> best
>
> Alex Sánchez
>
> ...............................................................................................................
> Dr. Alex  Sánchez.
> Associate Professor. Statistics Department. University of Barcelona.
> Facultat de Biologia UB. Avda Diagonal 645. 08028 Barcelona. Spain
> asanchez_at_ub.edu
> Statistics and Bioinformatics Unit
> Institut de Recerca. Hospital Universitari Vall 'Hebron
> Passeig Vall d'Hebron 112-119. 08034 Barcelona
> asanchez_at_ir.vhebron.net
> ...............................................................................................................
>
>
>
>
>
>
>> Message: 17
>> Date: Wed, 12 Aug 2009 09:10:56 +0200
>> From: Johannes Hanson <s.j.hanson at uu.nl>
>> Subject: [BioC] How to compare GO results
>> To: bioconductor at stat.math.ethz.ch
>> Message-ID: <02C00589-9261-449C-B8A4-D7C8C4986E72 at uu.nl>
>> Content-Type: text/plain; charset=US-ASCII; format=flowed; delsp=yes
>>
>> Dear all,
>>
>> This might not be a specific BioConductor question. However,
>> BioConductor is my major tool and therefore I ask the question here.
>> If not appropriate please ignore.
>>
>> I am analyzing array data from a set of mutants all showing the same
>> phenotype. The idea was of course to find genes similarly expressed  in
>> all mutants to get closer to the regulatory mechanism of the  phenotype.
>> Surprisingly there was nearly no overlap among the differentially
>> expressed genes. The suggestion was raised that the genes might  encode
>> similar functions. I therefore conducted GO analysis (using topGO and
>> other packages). Still very little obvious overlap but how to  quantify
>> it? How to determine the degree of similarity between different GO
>> results?
>>
>> All suggestions are welcome.
>>
>> Johannes Hanson
>> Molecular Plant Physiology, Utrecht University
>>
>>
>



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