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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Reducing GWAS complexity
Cell Cycle, Volume 15, No. 1, Year 2016
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Description
Genome-wide association studies (GWAS) have revealed numerous genomic ‘hits’ associated with complex phenotypes. In most cases these hits, along with surrogate genetic variation as measure by numerous single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium, are not in coding genes making assignment of functionality or causality intractable. Here we propose that fine-mapping along with the matching of risk SNPs at chromatin biofeatures lessen this complexity by reducing the number of candidate functional/causal SNPs. For example, we show here that only on average 2 SNPs per prostate cancer risk locus are likely candidates for functionality/causality; we further propose that this manageable number should be taken forward in mechanistic studies. The candidate SNPs can be looked up for each prostate cancer risk region in 2 recent publications in 20151,2 from our groups. © 2016 Taylor & Francis Group, LLC.
Authors & Co-Authors
Hazelett, Dennis J.
United States, Los Angeles
Cedars-sinai Medical Center
Conti, David V.
United States, Los Angeles
University of Southern California
Han, Ying
United States, Los Angeles
University of Southern California
Al Olama, Ali Amin
United Kingdom, Cambridge
University of Cambridge
d'Adamo, Adamo P.
United Kingdom, Cambridge
University of Cambridge
Eeles, Rosalind A.
United Kingdom, London
The Institute of Cancer Research
Kóte-Jarai, Zsofia S.
United Kingdom, London
The Institute of Cancer Research
Haiman, Christopher A.
United States, Los Angeles
University of Southern California
Coetzee, Gerhard A.
United States, Los Angeles
University of Southern California
United Kingdom, Cambridge
University of Cambridge
United Kingdom, London
The Institute of Cancer Research
United States
Van Andel Institute
Statistics
Citations: 15
Authors: 9
Affiliations: 5
Identifiers
Doi:
10.1080/15384101.2015.1120928
ISSN:
15384101
Research Areas
Cancer
Genetics And Genomics
Study Design
Case-Control Study