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    GenePattern Proteomics Module

    Category  Proteomics>Mass Spectrometry Analysis/Tools

    Abstract  GenePattern combines an advanced scientific workflow
    platform with more than 90 computational and visualization tools for the
    analysis of genomic/proteomic data.

    GenePattern Proteomics offers peak detection, noise subtraction, peak
    matching, and more for the advanced analysis of Matrix-Assisted Laser
    Desorption/Ionization (MALDI), Surface-Enhanced Laser
    Desorption/Ionization (SELDI), and Liquid Chromatography-Mass
    Spectrometry (LC-MS) data.

    GenePattern provides the following support for the analysis of
    proteomic data: 1) PEPPeR (LC-MS); 2) ProteoArray (LC-MS); & 3)
    SELDI/MALDI.

    1) PEPPeR (LC-MS) -- For the analysis of LC-MS data, GenePattern
    provides support for the algorithms defined by PEPPeR, a Platform for
    Experimental Proteomic Pattern Recognition:

    a) Landmark matching is a method to propagate identified peptides
    over time onto accurate mass LC-MS features in such a way as to
    maximize total identified peptides from disparate data acquisition
    methods. Using a combination of accurate mass and local retention
    time information it is possible to determine the likely identification of an
    unknown peak based on its relative location to known peaks.

    b) Peak matching attempts to group similar features (or peaks) across
    multiple LC-MS sample runs by incorporating m/z (mass-to-charge
    ratio) and retention time (RT) variation. Although peak matching can be
    performed on virtually any type of LC-MS data, it is typically performed
    after landmark matching.

    Note: The PEPPeR modules are based on work published by Jaffe,
    Mani, et al in PEPPeR, a Platform for Experimental Proteomic Pattern
    Recognition (Molecular & Cellular Proteomics 5:1927-1941, 2006).

    2) ProteoArray (LC-MS) -- GenePattern's 'ProteoArray module' provides
    the following support for the analysis of LC-MS data:

    a) For a series of LC-MS experiments in mzXML format [an XML
    (eXtensible Markup Language) based common file format for
    proteomics mass spectrometric data], GenePattern provides the ability
    to detect and align features across runs.

    Note: This module is provided by Brian Piening of the Fred Hutchinson
    Cancer Research Center.

    3) SELDI/MALDI -- GenePattern provides the following support for the
    analysis of SELDI/MALDI data:

    a) Quality assessment of the input spectrum as a function of the area
    under the spectrum and the area under the spectrum after removing the
    noise component of the signal.

    b) Peak detection using digital convolution (moving window) filters,
    which applies smoothing, background correction, and peak
    enhancement filters to the spectrum before identifying final peak
    locations.

    c) Spectra comparison, which filters the noise from two (2) spectra and
    then compares the spectra using a cross correlation function.

    d) A proteomics pipeline provides automated processing of
    SELDI/MALDI data. In addition to quality assessment and peak
    detection, the pipeline incorporates a range of normalization methods
    and sophisticated peak alignment algorithms for matching peaks
    across multiple samples.

    Starting with spectra from a set of samples, the pipeline outputs
    matched peaks as features, and normalized intensities of these peaks
    for each sample. Several aspects of the pipeline are fully customizable.

    e) Integration with other GenePattern analysis modules. By
    representing peaks as features, the peak detection and proteomics
    pipeline modules create output files similar to those used as input for
    the modules that support gene expression analysis (see G6G Product
    Number 20181).

    Analyses such as clustering, classification, and differential marker
    selection are based on pattern recognition and applicable to the
    analysis of both proteomic data and gene expression data.

    Note: The modules for the analysis of SELDI/MALDI data are based on
    work published by Mani and Gillette in Proteomic Data Analysis: Pattern
    Recognition for Medical Diagnosis and Biomarker Discovery (Mehmed
    Kantardzic and Jozef Zurada (Eds.) Next Generation of Data Mining
    Applications, Wiley-IEEE Press).

    Data Formats -- Proteomics analysis modules are designed for easy
    access:

    a) All proteomics modules read and write data using mzXML or comma-
    separated value (csv) files. Generally, mzXML files tend to be used for
    LC-MS data and csv files for SELDI/MALDI data.

    b) GenePattern provides support for data conversion (see G6G Product
    Number 20183), including support for converting to and from mzXML
    files.

    System Requirements  (from GenePattern 3.1 Release Notes)

    Supported operating systems: GenePattern installers are available for
    Windows, Mac OS X, and Linux. GenePattern should work with any
    operating system that has a Java 1.5 virtual machine installed. We have
    tested it on the following OS platforms:

    Windows        XP, Vista
    Mac        OS X 10.4 (Tiger), OS X 10.5 (Leopard)
    Linux        Ubuntu 7.10, SuSE

    Users are also running GenePattern on the Red Hat, Debian, Gentoo,
    Mandrake and Fedora distributions of Linux.

    Supported browsers: The GenePattern Web Client has been tested on
    the following browsers:

    Windows        Firefox 2.0, MS Internet Explorer 6.0 and 7.0
    Mac        Firefox 2.0, Safari 2.0
    Linux        Firefox 2.0
    Safari: By default, Safari sets an open "safe" files after downloading
    preference. This setting prevents GenePattern from correctly exporting
    and importing zip files. To clear this preference: open Safari, select
    Safari>Preferences, select General preferences, and clear the Open
    "safe" files after downloading check box.

    Current technology versions: Following are the technology versions
    used in GenePattern 3.1.
    Updated technologies are shown in bold face.
    o        Java 1.5
    o        R 2.5.0
    o        Perl 5.8.8
    o        Tomcat 5.5.* series
    o        HSQL 1.8.0

    Hardware requirements: GenePattern's hardware requirements are
    found on almost all currently available machines:
    o        256 MB RAM
    o        500 MHz Pentium 3 or equivalent
    o        Hard drive space:
            Server: 252 MB
            Client: 84 MB

    As of December 2007, installing all GenePattern modules from the
    Broad repository requires approximately 1 GB of hard drive space. The
    SNPFileCreator module may require additional RAM depending on the
    chip type and number of CEL files being processed.

    Manufacturer   

    Broad Institute of MIT and Harvard
    7 Cambridge Center
    Cambridge, MA 02142
    Ph: 617.452.3000
    Fax: 617.452.4588
    or
    320 Charles Street
    Cambridge, MA 02141-2023
    Ph: 617.258.0900
    Fax: 617.258.0901
    E-mail: gp-help@broad.mit.edu

    Manufacturer's Web Site  www.broad.mit.
    edu/cancer/software/genepattern/desc/proteomics.html

    Price   Contact manufacturer

    G6G Product Number  20182

    G6G Manufacturer Number 101795
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