CASMAP: detection of statistically significant combinations of SNPs in association mapping
File(s)
Published version
Author(s)
Llinares-López, Felipe
Papaxanthos, Laetitia
Roqueiro, Damian
Bodenham, Dean
Borgwardt, Karsten
Type
Journal Article
Abstract
Combinatorial association mapping aims to assess the statistical association of higher-order interactions of genetic markers with a phenotype of interest. This article presents combinatorial association mapping (CASMAP), a software package that leverages recent advances in significant pattern mining to overcome the statistical and computational challenges that have hindered combinatorial association mapping. CASMAP can be used to perform region-based association studies and to detect higher-order epistatic interactions of genetic variants. Most importantly, unlike other existing significant pattern mining-based tools, CASMAP allows for the correction of categorical covariates such as age or gender, making it suitable for genome-wide association studies.
Date Issued
2019-08-01
Date Acceptance
2018-12-10
Citation
Bioinformatics, 2019, 35 (15), pp.2680-2682
ISSN
1367-4803
Publisher
Oxford University Press (OUP)
Start Page
2680
End Page
2682
Journal / Book Title
Bioinformatics
Volume
35
Issue
15
Copyright Statement
© The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/),
which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact
journals.permissions@oup.com
which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact
journals.permissions@oup.com
Identifier
https://academic.oup.com/bioinformatics/article/35/15/2680/5239654/
Subjects
Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Publication Status
Published
Date Publish Online
2018-12-12