A GS-CORE algorithm for performing a reduction test on multiple gene sets and their core genes
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
Year of publication: |
2015
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Authors: | Yang, Tae |
Published in: |
Computational Statistics. - Springer. - Vol. 30.2015, 1, p. 29-41
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Publisher: |
Springer |
Subject: | Core genes | Enrichment score | False-discovery rate | Leading-edge subset |
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