Fast and accurate exhaustive higher-order epistasis search with BitEpi

Arash Bayat; Brendan Hosking; Yatish Jain; Cameron Hosking; Milindi Kodikara; Daniel Reti; Natalie A Twine; Denis C Bauer

doi:10.1038/s41598-021-94959-y

Fast and accurate exhaustive higher-order epistasis search with BitEpi

Sci Rep. 2021 Aug 5;11(1):15923. doi: 10.1038/s41598-021-94959-y.

Authors

Arash Bayat^{1

2}, Brendan Hosking¹, Yatish Jain^{1

3}, Cameron Hosking¹, Milindi Kodikara¹, Daniel Reti^{1

4}, Natalie A Twine^{1

4}, Denis C Bauer^{5

6

7}

Affiliations

¹ Transformations Bioinformatics, Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), North Ryde, NSW, 2113, Australia.
² The Kinghorn Cancer Centre, Darlinghurst, NSW, 2010, Australia.
³ Department of Biomedical Sciences, Macquarie University, Macquarie Park, NSW, 2113, Australia.
⁴ Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, 2113, Australia.
⁵ Transformations Bioinformatics, Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation (CSIRO), North Ryde, NSW, 2113, Australia. Denis.Bauer@CSIRO.au.
⁶ Department of Biomedical Sciences, Macquarie University, Macquarie Park, NSW, 2113, Australia. Denis.Bauer@CSIRO.au.
⁷ Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, 2113, Australia. Denis.Bauer@CSIRO.au.

Abstract

Complex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved. In this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.e. Single Nucleotide Variant or SNV for short). BitEpi introduces a novel bitwise algorithm that is 1.7 and 56 times faster for 3-SNV and 4-SNV search, than established software. The novel entropy statistic used in BitEpi is 44% more accurate to identify interactive SNVs, incorporating a p-value-based significance testing. We demonstrate BitEpi on real world data of 4900 samples and 87,000 SNPs. We also present EpiExplorer to visualize the potentially large number of individual and interacting SNVs in an interactive Cytoscape graph. EpiExplorer uses various visual elements to facilitate the discovery of true biological events in a complex polygenic environment.