Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies

Daniel J. Schaid, Jason P. Sinnwell, Gregory D. Jenkins, Shannon K. McDonnell, James N. Ingle, Michiaki Kubo, Paul E. Goss, Joseph P. Costantino, D. Lawrence Wickerham, Richard M. Weinshilboum

研究成果: ジャーナルへの寄稿学術論文査読

30 被引用数 (Scopus)

抄録

Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses.

本文言語英語
ページ(範囲)3-16
ページ数14
ジャーナルGenetic Epidemiology
36
1
DOI
出版ステータス出版済み - 01-2012
外部発表はい

All Science Journal Classification (ASJC) codes

  • 疫学
  • 遺伝学(臨床)

フィンガープリント

「Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル