ArticleBioinformatics (Oxford, England)2019
CASMAP: detection of statistically significant combinations of SNPs in association mapping.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Turning heterogeneity of statistical epistasis networks to an advantage.Briefings in bioinformatics · 2026Article
- GWASTool: A web pipeline for detecting SNP-phenotype associations.Fundamental research · 2024Article
- Network-guided search for genetic heterogeneity between gene pairs.Bioinformatics (Oxford, England) · 2021Article
- Enhancing statistical power in temporal biomarker discovery through representative shapelet mining.Bioinformatics (Oxford, England) · 2020Article
- Article
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Authors and funding
5 authors.
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Abstract
summaryCombinatorial 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. AVAILABILITY AND IMPLEMENTATION: The R and Python packages can be downloaded from our GitHub repository http://github.com/BorgwardtLab/CASMAP. The R package is also available on CRAN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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