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Efficient Algorithms for the Two Locus Problem in Genome-Wide Association Study: Algorithms for the Two Locus Problem

Authors:

Sanguthevar Rajasekaran,

Subrata SahaAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 2305 - 2310

https://doi.org/10.1145/2983323.2983685

Published: 24 October 2016 Publication History

Abstract

Advances made in sequencing technology have resulted in the sequencing of thousands of genomes. Novel analysis tools are needed to process these data and extract useful information. Such tools could aid in personalized medicine. As an example, we could identify the causes for a disease by comparing the genomes of people who have the disease and those who do not have this disease. Given that human variability happens due to single nucleotide polymorphisms (SNPs), we could focus our attention on these SNPs. Investigations that try to understand human variability using SNPs fall under genome-wide association study (GWAS). A crucial step in GWAS is the identification of the correlation between genotypes (SNPs) and phenotypes (i.e., characteristics such as the presence of a disease). This step can be modeled as the k-locus problem (where k is any integer). A number of algorithms have been proposed in the literature for this problem when k = 2. In this paper we present an algorithm for solving the 2-locus problem that is up to two orders of magnitude faster than the previous best known algorithms.

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Cited By

Rajasekaran SSaha S(2016)Efficient Algorithms for the Three Locus Problem in Genome-Wide Association Study2016 IEEE 16th International Conference on Data Mining (ICDM)10.1109/ICDM.2016.0152(1155-1160)Online publication date: Dec-2016
https://doi.org/10.1109/ICDM.2016.0152

Index Terms

Efficient Algorithms for the Two Locus Problem in Genome-Wide Association Study: Algorithms for the Two Locus Problem
1. Applied computing
  1. Life and medical sciences
    1. Bioinformatics
    2. Computational biology
      1. Molecular sequence analysis

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cover image ACM Conferences

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

Copyright © 2016 ACM.

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Published: 24 October 2016

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Cited By

Rajasekaran SSaha S(2016)Efficient Algorithms for the Three Locus Problem in Genome-Wide Association Study2016 IEEE 16th International Conference on Data Mining (ICDM)10.1109/ICDM.2016.0152(1155-1160)Online publication date: Dec-2016
https://doi.org/10.1109/ICDM.2016.0152

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