Journal article
Stability of bivariate GWAS biomarker detection
J Bedo, D Rawlinson, B Goudey, CS Ong
Plos One | PUBLIC LIBRARY SCIENCE | Published : 2014
Abstract
Given the difficulty and effort required to confirm candidate causal SNPs detected in genome-wide association studies (GWAS), there is no practical way to definitively filter false positives. Recent advances in algorithmics and statistics have enabled repeated exhaustive search for bivariate features in a practical amount of time using standard computational resources, allowing us to use cross-validation to evaluate the stability. We performed 10 trials of 2-fold cross-validation of exhaustive bivariate analysis on seven Wellcome-Trust Case-Control Consortium GWAS datasets, comparing the traditional x2 test for association, the high-performance GBOOST method and the recently proposed GSS sta..
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Awarded by Australian Research Council
Funding Acknowledgements
NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. This research was undertaken with the assistance of resources provided at the Multi-modal Australian Sciences Imaging and Visualisation Environment (MASSIVE) through the National Computational Merit Allocation Scheme supported by the Australian Government. This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113 and 085475. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.