Population‐Based Association and Gene by Environment Interactions in Genetic Analysis Workshop 18. Issue 1 (September 2014)

• Record Type: Journal Article
• Authors: Satten, Glen A.; Biswas, Swati; Papachristou, Charalampos; Turkmen, Asuman; König, Inke R.; Paterson, Andrew; Bickeböller, Heike; Almasy, Laura
• Is Part Of: Genetic epidemiology. Volume 38:Issue 1(2014)
• Page Start: S49
• Page End: S56
• Publication Date: 2014-09
• Subjects: Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.21825
• Languages: English
• ISSNs: 0741-0395

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p>In the past decade, genome‐wide association studies have been successful in identifying genetic loci that play a role in many complex diseases. Despite this, it has become clear that for many traits, investigation of single common variants does not give a complete picture of the genetic contribution to the phenotype. Therefore a number of new approaches are currently being investigated to further the search for susceptibility loci or regions. We summarize the contributions to Genetic Analysis Workshop 18 (GAW18) that concern this search using methods for population‐based association analysis. Many of the members of our GAW18 working group made use of data types that have only recently become available through the use of next‐generation sequencing technologies, with many focusing on the investigation of rare variants instead of or in combination with common variants. Some contributors used a haplotype‐based approach, which to date has been used relatively infrequently but may become more important for analyzing rare variant association data. Others analyzed gene‐gene or gene‐environment interactions, where novel statistical approaches were needed to make the best use of the available information without requiring an excessive computational burden. GAW18 provided participants with the chance to make use of state‐of‐the‐art data, statistical techniques, and technology. We report here some of the experiences and conclusions that were reached by workshop participants who analyzed the GAW18 data as a population‐based association study.</p> </abstract>