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  Two-locus association mapping in subquadratic time

Achlioptas, P., Schölkopf, B., & Borgwardt, K. (2011). Two-locus association mapping in subquadratic time. In C. Apté, J. Ghosh, & P. Smyth (Eds.), 17th ACM SIGKKD Conference on Knowledge Discovery and Data Mining (KDD 2011) (pp. 726-734). New York, NY, USA: ACM Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BAE8-A Version Permalink: https://hdl.handle.net/21.11116/0000-0006-C58E-C
Genre: Conference Paper

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https://dl.acm.org/citation.cfm?doid=2020408.2020521 (Publisher version)
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 Creators:
Achlioptas, P, Author           
Schölkopf, B1, Author           
Borgwardt, K2, Author           
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497647              
2Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497664              

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 Abstract: Genome-wide association studies (GWAS) have not been able to discover strong associations between many complex human diseases and single genetic loci. Mapping these phenotypes to pairs of genetic loci is hindered by the huge number of candidates leading to enormous computational and statistical problems. In GWAS on single nucleotide polymorphisms (SNPs), one has to consider in the order of 1010 to 1014 pairs, which is infeasible in practice. In this article, we give the first algorithm for 2-locus genome-wide association studies that is subquadratic in the number, n, of SNPs. The running time of our algorithm is data-dependent, but large experiments over real genomic data suggest that it scales empirically as n3/2. As a result, our algorithm can easily cope with n ~ 107, i.e., it can efficiently search all pairs of SNPs in the human genome.

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 Dates: 2011-08
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1145/2020408.2020521
BibTex Citekey: Borgwardt2011
 Degree: -

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Title: 17th ACM SIGKKD Conference on Knowledge Discovery and Data Mining (KDD 2011)
Place of Event: San Diego, CA, USA
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Title: 17th ACM SIGKKD Conference on Knowledge Discovery and Data Mining (KDD 2011)
Source Genre: Proceedings
 Creator(s):
Apté, C, Editor
Ghosh, J, Editor
Smyth, P, Editor
Affiliations:
-
Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 726 - 734 Identifier: ISBN: 978-1-4503-0813-7