PAGER 2.0: An update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

Zongliang Yue, Qi Zheng, Michael T. Neylon, Minjae Yoo, Jimin Shin, Zhiying Zhao, Aik Choon Tan, Jake Y. Chen

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)

    Abstract

    Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug-gene, miRNA-gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/.

    Original languageEnglish
    Pages (from-to)D668-D676
    JournalNucleic acids research
    Volume46
    Issue numberD1
    DOIs
    Publication statusPublished - 2018 Jan 1

    Bibliographical note

    Publisher Copyright:
    © 2017 The Author(s).

    ASJC Scopus subject areas

    • Genetics

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