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    GenePattern SNP Analysis & Data Format
    Conversion Modules

    Category  Genomics>Genetic Data Analysis/Tools

    Abstract  GenePattern combines an advanced scientific workflow
    platform with more than 90 computational and visualization tools for the
    analysis of genomic data. GenePattern SNP Analysis lets you analyze
    single nucleotide polymorphism (SNP) microarrays using
    normalization, copy number estimation, smoothing, Loss of
    Heterozygosity (LOH) determination, and visualization.

    High-density SNP arrays allow for the analysis of SNPs, copy number
    alterations (amplifications and deletions), and LOH detection.

    GenePattern provides the following support for the analysis of SNP
    microarray data:

    1) Scaling of the data to normalize intensity levels across microarray
    chips.

    2) Probe-level modeling to determine an intensity value for each SNP
    based on the intensity levels of the probes in each probe set.

    3) Copy number (CN) calculation to determine the copy number of a
    target SNP. The calculation, which divides the intensity value of the
    target SNP by the intensity value of the normal SNP, is also called CN
    normalization or normalization with respect to normals.

    4) Smoothing based on the R package GLAD (Gain and Loss Analysis
    of DNA), which detects the altered regions in the genomic pattern and
    assigns a status (normal, gained or lost) to each chromosomal region.

    5) Additional analyses to support detection and visualization of LOH and
    CN alterations.

    SNP Analysis sub-modules are as follows:

    a) Module Name is CopyNumberDivideByNormals -- Determines the
    copy number of a target SNP.

    b) Module Name is GLAD -- Gain and Loss Analysis of DNA.

    c) Module Name is LOHPaired -- Computes LOH for paired samples.

    d) Module Name is SNPFileCreator -- Process Affymetrix SNP probe-
    level data into an expression value.

    e) Module Name is SNPFileSorter -- Sorts a .snp file by Chromosome
    and location.

    f) Module Name is SNPMultipleSampleAnalysis -- Determine Regions
    of Concordant Copy Number Aberrations.

    g) Module Name is XChromosomeCorrect -- Corrects X Chromosome
    SNPs for male samples.

    Data Format Conversion Module -- Import and export data, normalize
    and filter data, convert gene identifiers, and more.

    Analyzing genomic data requires working with vast amounts of
    inherently noisy data in a variety of data formats, where gene identifiers
    can vary across platforms. In addition to supporting genomic analysis,

    GenePattern provides support for simply working with your data files.
    GenePattern provides the following support for essential data
    processing tasks:

    1) Importing, exporting, and file conversion: GenePattern imports data
    from a broad array of platforms and formats, including Microarray Gene
    Expression Markup Language (MAGE-ML), mzXML [an XML (eXtensible
    Markup Language) based common file format for proteomics mass
    spectrometric data], and the Gene Expression Omnibus (GEO) (see
    G6G Product Number 20013);

    Converts Affymetrix cell intensity (CEL) files to GenePattern files and
    GenePattern files to MAGE-ML format; and converts line endings to the
    format required by the host operating system.

    2) Normalizing, filtering, and imputing values: The 'preprocessDataset'
    module provides several pre-processing options, including
    normalization, floor and ceiling thresholding, and variation filtering.

    If your expression data set is missing values, GenePattern provides
    support for imputing those values; this can be particularly useful when
    converting cDNA expression data, which allows missing values, to a
    formats that do Not.

    3) Converting gene identifiers and retrieving annotations: GenePattern
    provides support for converting the gene identifiers used by one
    microarray chip to those used by another. It provides access to gene
    annotations through 'GeneCruiser', which uses Affymetrix probe (gene)
    identifiers.

    4) Working with data sets: GenePattern provides support for working
    with data sets by allowing you to extract row and column (gene and
    sample) names, extract rows and columns of data, transpose rows and
    columns, reorder samples based on phenotypes, or split a single data
    set into two (2) non-overlapping subsets.

    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
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