[Genome] (no subject)

Brooke Rhead rhead at soe.ucsc.edu
Tue Mar 6 15:17:54 PST 2007


Hello Jon,

You might consider using the Conservation track multiple alignment 
format (MAF) file instead of the individual net alignments.  MAF is 
described here:

http://genome.ucsc.edu/FAQ/FAQformat#format5

You can extract the regions of interest from a MAF file using the Table 
Browser by first making a custom track of the regions and then 
intersecting the Conservation track (the multiz17way table if using 
hg18) with your custom track.  You would then need to grep out your 
species of interest from the resulting MAF file.

Another option is to use Galaxy, a set of tools created and maintained 
by Penn State that work in conjunction with the Genome Browser, located 
here:

http://main.g2.bx.psu.edu/

They have several tools for dealing with MAFs.  In the "Fetch Sequences 
and Alignments" section on the left-hand side of the site, there are two 
tools that would be useful for your situation: "Extract MAF blocks -- 
given a set of genomic intervals" and "Maf Limit to Species -- Remove 
undesired species from a MAF file".

I hope this information is helpful.  Please let us know if you have any 
further questions.

-- 
Brooke Rhead
UCSC Genome Bioinformatics Group


JONATHAN COOPER wrote:
> Hi.
> 
> I am required for an Msc project to compare 1400 human RE1(repressor
> element 1) sites (each 21bp) against chimp, rat, & mouse genomes for
> sequence homology. Although i could  do this manually, it'd take me
> quite a while, & wouldn't be much fun. Could you please tell me - are
> there any scripts you know of that can do this for me? Failing that,
> can you suggest the most appropriate data to download to write a
> script for. At the moment i am considering using the "axtNet" genome
> alignments - but am not sure if it is the best format to use. All i
> really need is for a file to contain the most similar match to the
> sequences i give it (and possibly a blast score)
> 
> Thanks for your time, best regards, Jon. 
> _______________________________________________ Genome maillist  -
> Genome at soe.ucsc.edu http://www.soe.ucsc.edu/mailman/listinfo/genome


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