MSblender

From Marcotte Lab
Revision as of 13:18, 30 January 2011 by Taejoon (Talk | contribs)

Jump to: navigation, search

MSblender is a statistical tool for merging database search results from multiple database search engines for peptide identification based on a multivariate modelling approach. We will present this work at RECOMB-CP 2011 in March, 2011.

Contents

Authors

Prerequisites

(We tested our codes at Mac OSX (10.5 Leopard) and Ubuntu Linux (10.04 and later). We don't support MS Windows platform yet.) To run MSblender, you should install the following programs/packages on the machine.

  • python (2.5 or later)
  • gcc (we used version 4.4.3, but we believe that our ANSI-C based codes are not dependent on specific version of gcc).
  • GNU Scientific Library (version 1.13 or later)
    • If you use ubuntu (or debian) linux, install 'gsl-bin' and 'libgsl0-*' packages.
  • (Optional) matplotlib (python graph library). Only required for 'pre/plot-his_list.py' script.

Installation

  • Download source code from GitHub. Alternatively, you can download it from http://www.marcottelab.org/users/MSblender/src/MSblender-current.tgz .
  • Enter to 'c/' directory, and execute './compile' script. You should have GNU Scientific Library before running this script. It will generate 'msblender' and 'msblender.h.gch' files at the same directory.
  • That's it. Now you are ready to run MSblender.

How to use

MSblender is working in three steps: pre-processing, modelling and post-processing.

Pre-processing

First MSblender converts various search engine results into a unified tab-delimited text file called 'hit_list' format. Then it transfers 'hit_list' to MSblender modelling program input file.

Currently, MSblender supports the following search engine results (and scores).

For example, you can convert X!Tandem pepxml file to logE_hit_score as below:

$ ../src/MSblender-20110130/pre/tandem_pepxml-to-logE_hit_list.py test.tandem_k.pepxml 
Write test.tandem_k.logE_hit_list ... 

The hit_list file generated by this looks like as below:

# pepxml: test.tandem_k.pepxml
#Spectrum_id	Charge	PrecursorMz	MassDiff	Peptide	Protein	MissedCleavages	Score(-log10[E-value])
MSups_5ul.07228.07228.4	4	689.596425	0.004000	SLLSNVEGDNAVPMQHNNRPTQPLK	CAH1_HUMAN_UPS|P00915|5000|50000|260	0	1.795880
MSups_5ul.11647.11647.2	2	592.839650	0.000000	ADGLAVIGVLMK	
....

Citation

  • T. Kwon*, H. Choi*, C. Vogel, A.I. Nesvizhskii, and E.M. Marcotte, MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines. Submitted.

See also