Rasool Tahmasbi1, Matthew C Keller1,2. 1. Institute for Behavioral Genetics (IBG). 2. Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309, USA.
Abstract
MOTIVATION: Computer simulations are excellent tools for understanding the evolutionary and genetic consequences of complex processes that cannot be analytically predicted and for creating realistic genetic data. There are many software packages that simulate genetic data, but they are typically not fast or memory efficient enough to simulate realistic, individual-level genome-wide SNP/sequence data. RESULTS: GeneEvolve is a user-friendly and efficient population genetics simulator that handles complex evolutionary and life history scenarios and generates individual-level phenotypes and realistic whole-genome sequence or SNP data. GeneEvolve runs forward-in-time, which allows it to provide a wide range of scenarios for mating systems, selection, population size and structure, migration, recombination and environmental effects. The software is designed to use as input data from real or previously simulated phased haplotypes, allowing it to mimic very closely the properties of real genomic data. AVAILABILITY AND IMPLEMENTATION: GeneEvolve is freely available at https://github.com/rtahmasbi/GeneEvolve CONTACT: Rasool.Tahmasbi@Colorado.eduSupplementary information: Supplementary data are available at Bioinformatics online.
MOTIVATION: Computer simulations are excellent tools for understanding the evolutionary and genetic consequences of complex processes that cannot be analytically predicted and for creating realistic genetic data. There are many software packages that simulate genetic data, but they are typically not fast or memory efficient enough to simulate realistic, individual-level genome-wide SNP/sequence data. RESULTS: GeneEvolve is a user-friendly and efficient population genetics simulator that handles complex evolutionary and life history scenarios and generates individual-level phenotypes and realistic whole-genome sequence or SNP data. GeneEvolve runs forward-in-time, which allows it to provide a wide range of scenarios for mating systems, selection, population size and structure, migration, recombination and environmental effects. The software is designed to use as input data from real or previously simulated phased haplotypes, allowing it to mimic very closely the properties of real genomic data. AVAILABILITY AND IMPLEMENTATION: GeneEvolve is freely available at https://github.com/rtahmasbi/GeneEvolve CONTACT: Rasool.Tahmasbi@Colorado.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Authors: Marc Chadeau-Hyam; Clive J Hoggart; Paul F O'Reilly; John C Whittaker; Maria De Iorio; David J Balding Journal: BMC Bioinformatics Date: 2008-09-08 Impact factor: 3.169
Authors: Matt Jones; Matthew C Keller; Richard Border; Sean O'Rourke; Teresa de Candia; Michael E Goddard; Peter M Visscher; Loic Yengo Journal: Nat Commun Date: 2022-02-03 Impact factor: 17.694