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

نویسندگان

  • Yoichi Yamada
  • Ken-ichi Hirotani
  • Kenji Satou
  • Ken-ichiro Muramoto
چکیده

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. key words: microarray data set, differentially expressed genes, dataspecific GO terms, cell cycle

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عنوان ژورنال:
  • IEICE Transactions

دوره 92-D  شماره 

صفحات  -

تاریخ انتشار 2009