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    FDA/NCTR ArrayTrack

    Category  Genomics>Gene Expression Analysis/Profiling/Tools

    Abstract  ArrayTrack is an integrated suite designed for the
    management, analysis and interpretation of microarray experiment
    data. There are three (3) integrated components: a) a Minimum
    Information About A Microarray Experiment (MIAME) supportive
    database that stores and annotates essential information for an
    experiment; b) analysis tools with an intuitive user interface providing
    the ability to search, filter, apply statistical operations and graphically
    visualize data; and c) a number of libraries that provide gene
    annotation, protein function and pathway information that are directly
    hyperlinked within the data analysis process. ArrayTrack is publicly
    available. Product features/capabilities include:

    MIAME supportive Database --

    1) Accepts microarray data from various platforms and/or scanners.
    The upload function has been tested for six (6) platforms (Affymetrix,
    Agilent, GE Health Care, Applied Biosystems, Illumina and customized
    2-color array).

    2) Accommodates many toxicological parameters, such as dose,
    chemicals, treatment schedule, sacrifice time, etc.

    3) Accepts Affymetrics (Affy) data in the cell intensity (CEL) file format.
    Converts CEL file to probe set [Robust Multichip Averaging (RMA),
    DChip, Expresso, Plier, Plier + 16] file. You will need to install the R
    server from BioConductor to use this function.

    4) A high throughput data uploading (batch import) function is
    implemented, which uploads entire datasets of an experiment in a
    single procedure.

    5) A comprehensive reporting system was developed to provide a
    summary of variables associated with an experiment.

    6) The data security function allows data sharing both easily and safely.

    7) The data export function allows the user to export an original data
    file, image file, CEL file and also export multiple datasets in one
    spreadsheet.

    Analysis Tools --

    1) Seven (7) normalization methods (MAS5, RMA, dChip and Plier) are
    available for the Affymetrix CEL file. In addition, traditional normalization
    methods (LOWESS, Linear LOWESS, Total Intensity Normalization,
    Mean/Median Scaling and GenePix Mean Log Ratio Normalization,
    Quantile and Reference Average Comparison Normalization) are also
    implemented for both one- and two-channel microarray data.

    2) “T-Test” calculates p-values for each gene on the chip. This function
    contains the standard and Welch t-test as well as the permutation t-
    test for one and two-class samples.

    3) “ANOVA”, different from t-test, allows statistical testing on multiple
    groups and/or variables. Currently, only one-way ANOVA is available.
    High-dimension ANalysis Of VAriance (ANOVA) will be available soon.

    4) After obtaining p-values using t-test/ANOVA, ArrayTrack provides
    several methods to select a list of significant genes for further analysis
    or biological interpretation:
    a) Use of more stringent statistics, such as Banferroni
    correction, to select a list of genes.
    b) Use of the Benjamini-Hochberg method based False
    Discovery Rate (FDR) to identify a list of significant genes.
    c) Ranking genes based on p-value cut-off, fold-change,
    intensity cut-off or combinations thereof.
    d) Use of “Volcano Plot” to select a list of genes based on both
    p-value cut-off and fold-change.
    e) “P-Value Plot” determines a list of genes by adjusting the
    rates of false positives and false negatives.

    5) “Hierarchical Clustering Analysis” (HCA) is an unsupervised
    clustering approach to group samples based on the similarity of gene
    expression patterns. The gene name in the HCA is linked to the Gene
    library. The image of the HCA or a sub cluster can be saved.

    6) “Principal Component Analysis” (PCA) is another unsupervised
    learning method to investigate sample clustering based on gene
    expression profiles.

    7) “Correlation Matrix” computes the correlation coefficients of different
    arrays and displays the matrix visually. The result of the R value can be
    exported.

    8) Both “ScatterPlot” and “Mixed ScatterPlot” provide pair-wise scatter
    plot functions. The “ScatterPlot” is a function that is specifically applied
    to two-color array data by plotting cy3 intensity vs. cy5 intensity. “Mixed
    ScatterPlot” is a general pair-wise plotting function that allows plotting
    of any one measure (intensity or ratio) against another similar
    measure in the same experiment.

    9) “MA Plot” is another two-color array specific function, where the log
    intensity ratio M = log2(Cy5/Cy3) is plotted against the mean log
    intensity A = 0.5log2(Cy3xCy5). This function might provide better visual
    inspection of the concordance and quality of the two-color chip
    expression data than the scatter plot.

    10) “Virtual Array Viewer” displays expression data in the format of the
    original array image. This function reconstructs the original array
    image based on either the raw or normalized expression data and
    provides a visual representation of data for further exploration, analysis
    and interpretation. The function is applied to both one channel and two-
    channel data, including Affy data.

    11) “Rank Intensity Plot” sorts intensities of genes in a descending
    order along the y-axis, and each gene is given an ordinal number
    along the x-axis to reflect its relative position on a chip. The shape of
    the curves characterizes the general properties of the expression data
    and provides a general assessment of the quality of data. This function
    is particular useful to examine the quality of two-color array data. For
    example, if the green curve represents the cy3-labeled samples while
    the red curve represents the cy5-labeled samples, a well-balanced
    two-channel microarray data should show a superimposed or parallel
    distribution of the green and red lines, and the crossover of the green
    and red lines indicate an unbalanced bias between the two channels.

    12) “BarChart” allows comparison of the expression level of a gene
    across the array data within a single experiment or across multiple
    experiments and/or platforms.

    13) “VennDiagram” displays the overlapping among 2~3 gene lists.
    The user can draw the diagram by common ID (gene ID, Locus ID,
    Spot ID, etc.), common pathway, or common Gene Ontology (GO).

    14) “Quality Control” enables the evaluation of the overall quality of two-
    color array GenePix data using visual inspection, statistical metrics
    and experiment annotation.

    15) “Quality Filtering” provides a means to examine the quality of each
    spot in two-color array GenePix data.

    Number of Libraries --

    1) “IDConverter” allows conversion between about ten (10) different
    IDs used by various public databases, including GenBank, LocusLink,
    UniGene, IMAGE, and etc.

    2) “Gene Library” and “Protein Library” contain the functional
    information about genes, and proteins for facilitating microarray data
    interpretation. All of these data are derived from public databases,
    including LocusLink, GenBank, UniGene, SWISS-PROT, KEGG, etc.
    Users can quickly identify the functional information for a set of
    significant genes derived from analysis by searching these libraries as
    well as other similar libraries included in this category.

    3) “Pathway Library” provides a collection of pathways from KEGG and
    PathArt. Using this library, users can identify a list of statistically
    significant pathways (Fisher Exact Test) based on a list of genes,
    proteins or metabolites. This library is useful for genomics, proteomics
    and metabonomics/metabolomics research.

    3) “PathArt” (see G6G Product Number 20060) is commercial software
    that provides manually curated pathways (mainly regulatory and
    disease pathways) for the interpretation of microarray results.
    ArrayTrack is integrated with PathArt. You will need to purchase the
    PathArt license separately from its manufacturer to use this function in
    ArrayTrack.

    4) "KEGG" mainly contains metabolic pathways. ArrayTrack is
    integrated with KEGG. Although KEGG is a public pathway package,
    commercial users need to contact the manufacturer to acquire a KEGG
    license for accessing this function through ArrayTrack.

    5) “IPA” stands for Ingenuity Pathways Analysis (see G6G Product
    Number 20017). Ingenuity delivers systems biology expertise to
    biologists and bioinformaticians through pathways analysis software,
    genome-scale computable network databases and knowledge
    management services and infrastructure. The user needs to get a
    license from Ingenuity to log into IPA through ArrayTrack.

    6) “GOFFA” stands for Gene Ontology (GO) For Functional Analysis.
    Comprehensive tools are available in “GOFFA” to analyze microarray
    results using GO resources. For example, it is straightforward in
    GOFFA to determine the statistically significant GO terms
    corresponding to a list of genes derived from a microarray experiment
    using the Fisher Exact Test. The GOFFA in ArrayTrack provides GO
    path plot, pruned GO tree plot, all gene list and term clustering
    categorized by molecular function, biological process and cellular
    component.

    7) “IPI (International Protein Index) Library” is downloaded from the
    European Bioinformatics Institute (EBI) website. This is a non-
    redundant protein database that is particular useful for proteomics
    research.

    8) “Orthologene Library” contains data from the National Center for
    Biotechnology Information (NCBI) Homologene database by
    augmenting with other functional information from. This is a resource
    particularly useful for cross-species research based on gene
    homology.

    9) “Chip Library” contains all the microarray chips that are used to
    generate the data stored in the ArrayTrack database. The chips are
    organized according to species, manufacture and platform. The
    manufacture-provided information for each chip is also available,
    including sequence information, if provided.

    10) Both “Toxicant Library” and “EDKB Library” contain chemical
    structure together with toxicological endpoints. The chemicals can be
    directly mapped to various metabolic pathways. These libraries are
    useful for integrating traditional toxicology data with genomics data.
    Since chemicals with similar structures are likely to exhibit similar
    biological (or toxicological) activities, NCTR/FDA is also implementing
    an algorithm for assessing structure similarity of chemicals and
    exploring structure-toxicity relationship based on the substructure
    features and physicochemical properties derived from the structure.
    The “Toxicant Library” has been initially populated with data from the
    Carcinogenicity Potency Database and the “Endocrine Disruptor
    Knowledge Base (EDKB) Library” that contains data associated with
    endocrine disruptors.

    11) All the libraries in ArrayTrack are interlinked.

    System Requirements  ArrayTrack uses machine-independent
    technology. Most users access ArrayTrack through a web browser.
    Information on the system requirements for the locally installed version
    is available here .

    ArrayTrack is only available on CD. Before requesting a CD  please
    ensure you have the appropriate Oracle license for your institute to run
    the software.  You can request a CD by contacting Dr. Weida Tong at
    (870) 543-7142.

    You must have an Oracle license to run ArrayTrack locally.

    1. An ORACLE 9i (or above) server is recommended for the current
    version of ArrayTrack.

    2. ArrayTrack is a client-server application: a Java client as the
    application front-end and an ORACLE database as the data repository.
    You need to setup the server first and then install the client from our
    website (the detail instruction for installation will be available along
    with the CDs).

    3. System recommendations:
    1. A relatively fast desktop or laptop with 1.5G memory and 25G
    free space should be OK for most uses.
    2.  If ArrayTrack is intended for supporting a large group of
    users, a server with at least 2G memory and multiple SCSI (or
    fiber channel) drives is needed. The required disk space
    depends on the amount of data you might generate and upload
    into the ArrayTrack database.

    4. We strongly recommend that you work with an ORACLE database
    administrator and a system administrator during installation of the
    server. That is also beneficial on the long run to ensure the safety of
    the data and the proper use of the software. If you encounter any
    difficulty during installation or on maintaining the software, please
    contact us.

    Manufacturer   Home office; see web site for international locations.

    FDA/National Center for Toxicological Research (NCTR)
    3900 NCTR Road
    Jefferson, AR 72079
    Dr. Weida Tong 870-543-7142, weida.tong@fda.hhs.gov
    Support: NCTRbioinformaticsSupport@nctr.fda.gov

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