In this work we show that in genome-wide association studies (GWAS) there is a strong bias favoring of genes covered by larger numbers of SNPs. Thus, we state here that there is a need for correction for such bias when performing downstream gene-level analysis, e.g. pathway analysis and gene-set analysis. We investigate several methods of obtaining gene level statistical significance in GWAS, and compare their effectiveness in correcting such bias. We also propose a simple algorithm based on first order statistic that corrects such bias. © 2012 Mirina et al.
CITATION STYLE
Mirina, A., Atzmon, G., Ye, K., & Bergman, A. (2012). Gene Size Matters. PLoS ONE, 7(11). https://doi.org/10.1371/journal.pone.0049093
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