An Identification Method of Data-Specific GO Terms from a Microarray Data Set

Access this Article

Search this Article

Author(s)

    • YAMADA Yoichi
    • Division of Electrical Engineering and Computer Science, Graduate School of Natural Science and Technology, Kanazawa University
    • HIROTANI Ken-ichi
    • Division of Electrical Engineering and Computer Science, Graduate School of Natural Science and Technology, Kanazawa University
    • SATOU Kenji
    • Division of Electrical Engineering and Computer Science, Graduate School of Natural Science and Technology, Kanazawa University
    • MURAMOTO Ken-ichiro
    • Division of Electrical Engineering and Computer Science, Graduate School of Natural Science and Technology, Kanazawa University

Abstract

Microarray technology has been applied to various biological and medical research fields. A preliminary step to extract any information from a microarray data set is to identify differentially expressed genes between microarray data. The identification of the differentially expressed genes and their commonly associated GO terms allows us to find stimulation-dependent or disease-related genes and biological events, etc. However, the identification of these deregulated GO terms by general approaches including gene set enrichment analysis (GSEA) does not necessarily provide us with overrepresented GO terms in specific data among a microarray data set (i.e., data-specific GO terms). In this paper, we propose a statistical method to correctly identify the data-specific GO terms, and estimate its availability by simulation using an actual microarray data set.

Journal

  • IEICE Transactions on Information and Systems

    IEICE Transactions on Information and Systems 92(5), 1093-1102, 2009-05-01

    The Institute of Electronics, Information and Communication Engineers

References:  15

Codes

Page Top