Gene Size Matters

Alexandra Mirina, Gil Atzmon, Qian K. Ye, Aviv Bergman

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Article numbere49093
JournalPLoS One
Volume7
Issue number11
DOIs
StatePublished - Nov 9 2012

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Genes
Genome-Wide Association Study
genes
Single Nucleotide Polymorphism
statistics
Statistics
genome-wide association study
methodology

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Gene Size Matters. / Mirina, Alexandra; Atzmon, Gil; Ye, Qian K.; Bergman, Aviv.

In: PLoS One, Vol. 7, No. 11, e49093, 09.11.2012.

Research output: Contribution to journalArticle

Mirina, Alexandra ; Atzmon, Gil ; Ye, Qian K. ; Bergman, Aviv. / Gene Size Matters. In: PLoS One. 2012 ; Vol. 7, No. 11.
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