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.
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Acknowledgments
This research was supported by Basic Science Research Program (NRF-2010-0009461 and NRF-2011-0016383) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education and Ministry of Science, ICT & Future Planning.
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Yang, T.Y. A GS-CORE algorithm for performing a reduction test on multiple gene sets and their core genes. Comput Stat 30, 29–41 (2015). https://doi.org/10.1007/s00180-014-0519-9
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DOI: https://doi.org/10.1007/s00180-014-0519-9