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CRT home > TissueInfo: Proteins Tutorial

To predict the tissue distribution of a set of protein sequences, follow these steps:

Obtain a FASTA file with the query sequences of the proteins. Use the proteins.fasta file as an example. This file will be referenced henceforth as query.fasta.
Make sure query.fasta provides a unique accession code for each protein. (The accession code is used to analyse the results.)

Search dbEST for ESTs that match the query sequences. As query sequences are protein sequences, we have to use BLAST. We can search the EST database with BLAST and convert the output to a tiac file in one step, using tisearch. tisearch -seqs query.fasta -tiac proteins -protein -db est

Query the proteins.tiac file for tissue information. The following command requests a few calculations to be performed for each query sequence found in the tiac file. tiquery -tiac proteins.tiac -out proteins -mostExpressedIn \ -report -numPlant \ -tissueSummary

Check out the results. The last step should have created three files: proteins.data, proteins.schema, proteins.report.

News

Jul, 2009; ChIPseeqer, a comprehensive framework for analysis of ChIP-seq data developed in the Elemento lab, is now available for download. [More]
Apr, 2009; The BDVal program developed by the Campagne laboratory for MAQC-II is now available from http://bdval.org. The software supports the development and evaluation of predictive biomarker models from high-throughput data. The web site offers binary and source distributions. [More]
Jan, 2009; Twease now supports searching MEDLINE articles by Author, Journal, and Publication Year. Examples for performing these searches can be found in the updated Twease tutorial. [More]

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Dec 11th; 4:00pm-5:00pm: Institute for Computational Biomedicine Research in Progress Seminar Series - Fabien Campagne; ICB Conference Room - Y.1301
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