GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm

@inproceedings{Bottolo2013GUESSingPA,
  title={GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm},
  author={Leonardo Bottolo and Marc Chadeau-Hyam and David I. Hastie and Tanja Zeller and Benoit Liquet and Paul Newcombe and Loic Yengo and Philipp S Wild and Arne Schillert and Andreas Ziegler and Sune Fallgaard Nielsen and Adam S. Butterworth and Weang Kee Ho and Rapha{\"e}le Castagn{\'e} and Thomas Munzel and David Tregouet and Mario Falchi and François Cambien and B{\o}rge G. Nordestgaard and Fr{\'e}d{\'e}ric Fumeron and Georg Schett and Philippe Froguel and John Danesh and Enrico Petretto and Stefan S Blankenberg and Laurence Tiret and Sylvia Richardson},
  booktitle={PLoS genetics},
  year={2013}
}
Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we… CONTINUE READING

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