A GS-CORE algorithm for performing a reduction test on multiple gene sets and their core genes

Tae Yang ()

Computational Statistics, 2015, vol. 30, issue 1, 29-41

Abstract: Gene-set analysis seeks to identify enriched gene sets that are strongly associated with the phenotype. In many applications, only a small subset of core genes in each enriched gene set is likely associated with the phenotype. The reduction of enriched gene sets to the corresponding leading-edge subsets of core genes is a useful way for biologists to understand the biological processes underlying the association of a gene set with the phenotype of interest. Therefore, we propose a new gene-set analysis that tests the significance of enrichment on multiple gene sets, while simultaneously determining the corresponding leading-edge subsets of core genes. In the proposed analysis, we assigned a newly defined enrichment score to each gene set, and then corrected the statistical significance of the score for multiple testing of many gene sets by controlling the false-discovery rate. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Core genes; Enrichment score; False-discovery rate; Leading-edge subset (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:30:y:2015:i:1:p:29-41

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DOI: 10.1007/s00180-014-0519-9

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