rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating

Richard Border; Osman Asif Malik

doi:10.1186/s12859-023-05442-6

rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating

BMC Bioinformatics. 2023 Aug 18;24(1):314. doi: 10.1186/s12859-023-05442-6.

Authors

Richard Border^#¹, Osman Asif Malik^#²

Affiliations

¹ Neurology and Computer Science, University of California, Los Angeles, 675 Charles E Young Dr S, Los Angeles, CA, 90095, USA. border.richard@gmail.com.
² Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA.

^# Contributed equally.

Abstract

Existing methods for generating synthetic genotype data are ill-suited for replicating the effects of assortative mating (AM). We propose rb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution. The rBahadur R library is available through the Comprehensive R Archive Network at https://CRAN.R-project.org/package=rBahadur .

Keywords: Assortative mating; Genotype simulation; Multivariate Bernoulli.

MeSH terms

Algorithms*
Binomial Distribution
Cell Communication*
Computer Simulation
Genotype