A novel significance score for gene selection and ranking | Zendy

Yufei Xiao | Zendy; Tzu-Hung Hsiao | Zendy; Uthra Suresh | Zendy; Hung-I Harry Chen | Zendy; Xiaowu Wu | Zendy; Steven E. Wolf | Zendy; Yidong Chen | Zendy

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A novel significance score for gene selection and ranking

Author(s) -

Yufei Xiao,

Tzu-Hung Hsiao,

Uthra Suresh,

Hung-I Harry Chen,

Xiaowu Wu,

Steven E. Wolf,

Yidong Chen

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr671

Subject(s) - ranking (information retrieval) , relevance (law) , statistic , value (mathematics) , gene , p value , computer science , gene selection , computational biology , statistical significance , selection (genetic algorithm) , multiple comparisons problem , receiver operating characteristic , statistical hypothesis testing , gene expression , data mining , bioinformatics , biology , statistics , genetics , machine learning , mathematics , microarray analysis techniques , political science , law

When identifying differentially expressed (DE) genes from high-throughput gene expression measurements, we would like to take both statistical significance (such as P-value) and biological relevance (such as fold change) into consideration. In gene set enrichment analysis (GSEA), a score that can combine fold change and P-value together is needed for better gene ranking.

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