Journal article

Accurate and Robust Genomic Prediction of Celiac Disease Using Statistical Learning

Gad Abraham, Jason A Tye-Din, Oneil G Bhalala, Adam Kowalczyk, Justin Zobel, Michael Inouye

PLoS Genetics | PUBLIC LIBRARY SCIENCE | Published : 2014


Awarded by WTCCC award

Awarded by Victorian Life Sciences Computation Initiative

Awarded by Wellcome Trust

Awarded by NHMRC

Funding Acknowledgements

The celiac disease genotype data was generated under WTCCC award WT084743 and Coeliac UK funding. Part of this work utilized the computing resources of the Victorian Life Sciences Computation Initiative (project VR0126). 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 Funding for the project was provided by the Wellcome Trust under award 076113 and 085475. MI was supported by an NHMRC early career fellowship 637400. MI and GA were supported by University of Melbourne funding. JATD was supported by an NHMRC Postgraduate Medical Scholarship. This work was partially supported by the Australian Research Council, and by the NICTA Victorian Research Laboratory. NICTA is funded by the Australian Government as represented by the Department of Broadband, Communications, and the Digital Economy, and the Australian Research Council through the ICT Centre of Excellence program. This work was made possible through Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIIS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.