𝔖 Bobbio Scriptorium
✦   LIBER   ✦

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

✍ Scribed by 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

Publisher
John Wiley and Sons
Year
2011
Tongue
English
Weight
177 KB
Volume
36
Category
Article
ISSN
0741-0395

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

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.

📜 SIMILAR VOLUMES

Increasing the power of identifying gene
Increasing the power of identifying gene × gene interactions in genome-wide association studies
✍ Charles Kooperberg; Michael LeBlanc 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 168 KB 👁 2 views

## Abstract In this paper we investigate the power to identify gene × gene interactions in genome‐wide association studies. In our analysis we focus on two‐stage analyses: analyses in which we only test for interactions between single nucleotide polymorphisms that show some marginal effect. We give

Sample size requirements to detect gene-
Sample size requirements to detect gene-environment interactions in genome-wide association studies
✍ Cassandra E. Murcray; Juan Pablo Lewinger; David V. Conti; Duncan C. Thomas; W. 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 209 KB 👁 2 views

Many complex diseases are likely to be a result of the interplay of genes and environmental exposures. The standard analysis in a genome-wide association study (GWAS) scans for main effects and ignores the potentially useful information in the available exposure data. Two recently proposed methods t

A novel haplotype-sharing approach for g
A novel haplotype-sharing approach for genome-wide case-control association studies implicates the calpastatin gene in Parkinson's disease
✍ Andrew S. Allen; Glen A. Satten 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 285 KB 👁 2 views

## Abstract The large number of markers considered in a genome‐wide association study (GWAS) has resulted in a simplification of analyses conducted. Most studies are analyzed one marker at a time using simple tests like the trend test. Methods that account for the special features of genetic associ

Using cases to strengthen inference on t
Using cases to strengthen inference on the association between single nucleotide polymorphisms and a secondary phenotype in genome-wide association studies
✍ Huilin Li; Mitchell H. Gail; Sonja Berndt; Nilanjan Chatterjee 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 142 KB 👁 2 views

## Abstract Case‐control genome‐wide association studies provide a vast amount of genetic information that may be used to investigate secondary phenotypes. We study the situation in which the primary disease is rare and the secondary phenotype and genetic markers are dichotomous. An analysis of the