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Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits

1
Department of Diagnostics and Therapeutics of Intractable Diseases, Juntendo University, Bunkyo-ku, Tokyo 113-8421, Japan
2
Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10065, USA
3
Department of Anatomy, Faculty of Medical Science, Naresuan University, Phitsanulok 65000, Thailand
4
Department of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada
5
Laboratory of the Biology of Addictive Diseases, Rockefeller University, New York, NY 10065, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Santiago Rodriguez
Genes 2021, 12(8), 1160; https://doi.org/10.3390/genes12081160
Received: 24 June 2021 / Revised: 23 July 2021 / Accepted: 27 July 2021 / Published: 28 July 2021
(This article belongs to the Section Human Genomics and Genetic Diseases)
Some genetic diseases (“digenic traits”) are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes, while the occurrence of only one such variant results in a normal phenotype. Detecting variant pairs underlying digenic traits by standard genetic methods is difficult and is downright impossible when individual variants alone have minimal effects. Frequent pattern mining (FPM) methods are known to detect patterns of items. We make use of FPM approaches to find pairs of genotypes (from different variants) that can discriminate between cases and controls. Our method is based on genotype patterns of length two, and permutation testing allows assigning p-values to genotype patterns, where the null hypothesis refers to equal pattern frequencies in cases and controls. We compare different interaction search approaches and their properties on the basis of published datasets. Our implementation of FPM to case-control studies is freely available. View Full-Text
Keywords: pattern mining; digenic traits; genotype pattern; diplotype pattern mining; digenic traits; genotype pattern; diplotype
MDPI and ACS Style

Okazaki, A.; Horpaopan, S.; Zhang, Q.; Randesi, M.; Ott, J. Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits. Genes 2021, 12, 1160. https://doi.org/10.3390/genes12081160

AMA Style

Okazaki A, Horpaopan S, Zhang Q, Randesi M, Ott J. Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits. Genes. 2021; 12(8):1160. https://doi.org/10.3390/genes12081160

Chicago/Turabian Style

Okazaki, Atsuko, Sukanya Horpaopan, Qingrun Zhang, Matthew Randesi, and Jurg Ott. 2021. "Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits" Genes 12, no. 8: 1160. https://doi.org/10.3390/genes12081160

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