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Old 02-15-2014, 08:42 PM   #1
NGS_New_User
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Exclamation Blastn Results - analysis

Hi Everyone,

I have done some blasting on a draft genome that I assembled de novo(~300,000 contigs) and now I want to analyze the results. I used blastn, and I really want to see what was found in the blast results. Blast2GO doesn't help with this (I believe its because I didn't blastx or blastp)

SO, my question is, can anyone give me an idea on what program I can use to manipulate/analyze the results so that I can look at the stats of the top hits, etc?
My blastn results are in tabular format. Any ideas will be extremely helpful.

Thank you!
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Old 02-16-2014, 01:48 PM   #2
maubp
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Originally Posted by NGS_New_User View Post
I used blastn, ... Blast2GO doesn't help with this (I believe its because I didn't blastx or blastp)
Correct, Blast2GO wants either BLASP or BLASTX against the NR protein database.
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Old 02-16-2014, 01:50 PM   #3
maubp
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Originally Posted by NGS_New_User View Post
SO, my question is, can anyone give me an idea on what program I can use to manipulate/analyze the results so that I can look at the stats of the top hits, etc?
My blastn results are in tabular format. Any ideas will be extremely helpful.
What kind of stats? If you just want the top hit, you can tell BLAST to only give you one hit per query.
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Old 02-17-2014, 07:20 AM   #4
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What kind of stats? If you just want the top hit, you can tell BLAST to only give you one hit per query.
The kind of summary stats I am aiming for or rather looking to extract is kinda similar of what is outputted by blast2go, ie in terms of top hit species and species distribution.
So, I was wondering if there is any other program out there that I can feed the BlastN results to get the stats. Or if anyone has a script to share that I can use to manipulate the data and extract such results.
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Old 02-17-2014, 07:43 AM   #5
maubp
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BLAST 2.2.28+ or later has the option of outputting the species name in the tabular output:
http://blastedbio.blogspot.co.uk/201...criptions.html

You might also be interested in "blobology" from the Blaxter lab:
https://github.com/blaxterlab/blobology
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