Human Gene Correlation Analysis: A Tool for the Identification of Transcriptionally Co-Expressed Genes

    June 2012 in “ BMC Research Notes ”
    Ioannis Michalopoulos, Georgios A. Pavlopoulos, Apostolos Malatras, Alexandros Karelas, Myrto Kostadima, Reinhard Schneider, Σοφία Κοσσίδα
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    Studysummary This study outlines the Human Gene Correlation Analysis tool, which classifies human genes by coexpression levels and identifies overrepresented annotation terms in correlated gene groups, with no new clinical results reported.
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    The document from June 6, 2012, introduces the Human Gene Correlation Analysis (HGCA) tool, which is used to identify transcriptionally co-expressed genes in humans. The HGCA tool calculates the Pearson Correlation Coefficient between probe set signal values from Affymetrix Human Genome Microarray samples, clusters genes using the Neighbour Joining method, and uses a hyper-geometric distribution to identify overrepresented terms in gene annotations. The tool was tested on a dataset of 4,452 samples from 62 different tissues/organs, confirming the co-expression of ribosomal proteins and identifying co-expressed genes for HLA and metallothionein proteins. The HGCA tool, available online, is useful for classifying genes by coexpression and predicting gene function, and it includes a user-friendly web interface for searching and analyzing gene correlations.
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