R help - Oct 2011 - Comparing two gff/gtf files : de novo transcripts v/s reference

Hi All

I am wondering if people based on their experience could share what methods
one could use to compare two gff/gtf files. The reason why I want to do so
is that we have constructed a RNA-Seq based transcriptome  and would like to
compare it with reference transcriptome we had from in-silico approaches.
Ideally we are looking to find out

1. new genes  we see
2. transcripts where the start/end side is changed (upstream/downstream)
3. possible gene fusions may be because in-silico approaches were not
correct

I know some of these could be resolved with BedTools but just wondering if
Bioconductor has anything specific built in coz each time it pleasantly
surprises me.

Thanks!
-Abhi

	[[alternative HTML version deleted]]

On 10/24/2011 02:23 PM, Abhishek Pratap wrote:
> Hi All
>
> I am wondering if people based on their experience could share what methods
> one could use to compare two gff/gtf files. The reason why I want to do so
> is that we have constructed a RNA-Seq based transcriptome  and would like
to
> compare it with reference transcriptome we had from in-silico approaches.
> Ideally we are looking to find out
>
> 1. new genes  we see
> 2. transcripts where the start/end side is changed (upstream/downstream)
> 3. possible gene fusions may be because in-silico approaches were not
> correct
>
> I know some of these could be resolved with BedTools but just wondering if
> Bioconductor has anything specific built in coz each time it pleasantly
> surprises me.
Hi Abhi --

better to ask on the Bioconductor mailing list

http://bioconductor.org/help/mailing-list/

where people will point to rtracklayer to import() gff files, and 
GenomicRanges to do the types of comparisons you're interested in. These 
will generally be fun and performant tools.

Martin
>
> Thanks!
> -Abhi
>
> 	[[alternative HTML version deleted]]
>
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-- 
Computational Biology
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109

Location: M1-B861
Telephone: 206 667-2793

did u try CummeRbund?
http://compbio.mit.edu/cummeRbund/

best,
ib



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