C
Chris Haley
Researcher at University of Edinburgh
Publications - 427
Citations - 26040
Chris Haley is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Quantitative trait locus & Population. The author has an hindex of 71, co-authored 410 publications receiving 23592 citations. Previous affiliations of Chris Haley include Medical Research Council & The Roslin Institute.
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Characterisation of genome-wide association epistasis signals for serum uric acid in human population isolates.
Wenhua Wei,Gibran Hemani,Andrew A. Hicks,Veronique Vitart,Claudia Cabrera-Cardenas,Pau Navarro,Jennifer E. Huffman,Caroline Hayward,Sara Knott,Igor Rudan,Peter P. Pramstaller,Sarah H. Wild,James F. Wilson,Harry Campbell,Malcolm G. Dunlop,Nicholas D. Hastie,Alan F. Wright,Chris Haley +17 more
TL;DR: It is concluded that GWA epistasis analysis is useful despite relatively low power in small isolated populations because gene ontology terms enriched by the epistasis signals in each population support links between SUA levels and neurological disorders.
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Genetic components of carcass and meat quality traits in Meishan and Large White pigs and their reciprocal crosses
TL;DR: Significant direct additive genetic differences between female genotypes were found for fat firmness, fat separation and drip loss, but these effects may in part have been a consequence of subcutaneous fat depth differences between genotypes.
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Regional variation in health is predominantly driven by lifestyle rather than genetics
Carmen Amador,Charley Xia,Reka Nagy,Archie Campbell,David J. Porteous,Blair H. Smith,Blair H. Smith,Nicholas D. Hastie,Veronique Vitart,Caroline Hayward,Pau Navarro,Chris Haley +11 more
TL;DR: It is shown that regional variation of obesity-related traits in a Scottish population is influenced more by lifestyle differences than it is by genetic differences, suggesting that inequalities can be tackled with appropriate social and economic interventions.
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Prediction of IBD based on population history for fine gene mapping
TL;DR: In this paper, a multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history.