๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Testing Gene-Gene Interactions in Genome Wide Association Studies

โœ Scribed by Hu, Jie Kate; Wang, Xianlong; Wang, Pei


Book ID
121646177
Publisher
John Wiley and Sons
Year
2014
Tongue
English
Weight
418 KB
Volume
38
Category
Article
ISSN
0741-0395

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Rapid testing of gene-gene interactions
โœ Kanishka Bhattacharya; Mark I. McCarthy; Andrew P. Morris ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 142 KB ๐Ÿ‘ 2 views

Genome-wide association (GWA) studies have been extremely successful in identifying novel loci contributing effects to a wide range of complex human traits. However, despite this success, the joint marginal effects of these loci account for only a small proportion of the heritability of these traits

Increasing the power of identifying gene
โœ Charles Kooperberg; Michael LeBlanc ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 168 KB ๐Ÿ‘ 2 views

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

Detecting gene-environment interactions
โœ Corinne D. Engelman; James W. Baurley; Yen-Feng Chiu; Bonnie R. Joubert; Juan P. ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 93 KB ๐Ÿ‘ 2 views

## Abstract Despite the importance of geneโ€environment (Gร—E) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genomeโ€wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 con

Sample size requirements to detect gene-
โœ Cassandra E. Murcray; Juan Pablo Lewinger; David V. Conti; Duncan C. Thomas; W. ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 209 KB ๐Ÿ‘ 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