ArticleFrontiers in genetics2023
A multi-threaded approach to genotype pattern mining for detecting digenic disease genes.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Benchmark of computational methods to detect digenism in sequencing data.European journal of human genetics : EJHG · 2025Review
- Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.Medical research archives · 2023Article
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4 authors.
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Abstract
To locate disease-causing DNA variants on the human gene map, the customary approach has been to carry out a genome-wide association study for one variant after another by testing for genotype frequency differences between individuals affected and unaffected with disease. So-called digenic traits are due to the combined effects of two variants, often on different chromosomes, while individual variants may have little or no effect on disease. Machine learning approaches have been developed to find variant pairs underlying digenic traits. However, many of these methods have large memory requirements so that only small datasets can be analyzed. The increasing availability of desktop computers with large numbers of processors and suitable programming to distribute the workload evenly over all processors in a machine make a new and relatively straightforward approach possible, that is, to evaluate all existing variant and genotype pairs for disease association. We present a prototype of such a method with two components,
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