[BioC] Ontology

Marc Carlson mcarlson at fhcrc.org
Mon Feb 3 20:45:12 CET 2014


Hi Orcun,

Now that you have told us a bit more about what you are doing it sounds 
a bit like you might want to just annotate some genes. That is, you 
started with sequences, but then you used BLAST to match them to known 
genes.  Once you have IDs for features on a genome, you can tap into 
older annotations that associated genes with GO terms.  Here I will give 
a simple example that assumes you are working with humans).  So for 
example, if you has a set of refseq IDs like this:

ids <- c("NP_000005","NP_570602")

## Then you could get the GO IDs that go with these refseq IDs like this:
library(Homo.sapiens)
select(Homo.sapiens, keys=ids, columns="GO", keytype="REFSEQ")

Hope this helps,

  Marc



On 01/31/2014 12:50 PM, Orcun Hacariz wrote:
> Many thanks for the information.
>
>
> On Fri, Jan 31, 2014 at 10:22 PM, Steve Lianoglou
> <lianoglou.steve at gene.com>wrote:
>
>> Hi,
>>
>> On Fri, Jan 31, 2014 at 12:14 PM, Orcun Hacariz <orcunhacariz at gmail.com>
>> wrote:
>>> Hi,
>>>
>>> My question is how to do a GO analysis with 'genes' using bioconductor
>>> tools.
>> OK, in this case there are several packages that you can use to do
>> different types of GO analyses. You can browse the package available
>> in bioconductor here:
>>
>> http://bioconductor.org/packages/release/BiocViews.html#___Software
>>
>> To make it easier to do so, the bioc-folks have enabled packages to be
>> tagged by functionality.
>>
>> There is a drill-down menu on the left hand side of the page you can
>> use to navigate these tags (aka "Views"). Dig down to:
>>
>>      Software > Annotation > GO
>>
>> To filter packages that were annotated to work w/ gene ontologies.
>>
>> You might try to start with either GOstats or goProflies.
>>
>> Each package has one (or more) vignettes detailing how they are used
>> in an analysis, which should get you started.
>>
>> HTH,
>> -steve
>>
>> --
>> Steve Lianoglou
>> Computational Biologist
>> Genentech
>>
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>
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