Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results

Most published GWAS do not examine SNP interactions due to the high computational complexity of computing p-values for the interaction terms. Our aim is to utilize supercomputing resources to apply complex statistical techniques to the world's accumulating GWAS, epidemiology, survival and patho...

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Bibliographic Details

Published in:	2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2012; pp. 1258 - 1261
Main Authors:	Reumann, M., Makalic, E., Goudey, B. W., Inouye, M., Bickerstaffe, A., Bui, M., Park, D. J., Kapuscinski, M. K., Schmidt, D. F., Zhou, Z., Qian, G., Zobel, J., Wagner, J., Hopper, J. L.
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.01.2012
Subjects:	Bayes Theorem Bayesian methods Bioinformatics Computational Biology - methods Computer Simulation Genome-Wide Association Study - methods Genomics Humans Monte Carlo Method Neoplasms - genetics Phenotype Polymorphism, Single Nucleotide Runtime
ISBN:	1424441196, 9781424441198
ISSN:	1094-687X, 1557-170X, 2694-0604, 2694-0604
Online Access:	Get full text
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