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SimBit:一款高性能、灵活且易于使用的群体遗传模拟器。

SimBit: A high performance, flexible and easy-to-use population genetic simulator.

机构信息

Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada.

Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.

出版信息

Mol Ecol Resour. 2021 Jul;21(5):1745-1754. doi: 10.1111/1755-0998.13372. Epub 2021 Mar 27.

Abstract

SimBit is a general purpose, high performance forward-in-time population genetics simulator. SimBit can simulate a wide variety of selection scenarios (any selection and dominance coefficients variation, any epistatic interaction, any spatial and temporal changes of selection scenario, etc.), demographic scenarios (any changes in patch sizes, migration rates, realistic demography dependent on fecundity, hard vs. soft selection, exponential vs. logistic growth, gametic or zygotic dispersion, etc.) and mating systems (cloning and selfing rates, hermaphrodites or males and females). SimBit can also track QTLs (with hyperdimensional phenotypes, explicit fitness landscape, plasticity, developmental noise, etc.). Finally, SimBit can simulate multiple species with their ecological relationships. SimBit comes with a R wrapper that simplifies the management of an entire research project from the creation of a grid of parameters and corresponding inputs, running simulations and gathering outputs for analysis. SimBit's performance was extensively benchmarked in comparison to SLiM, Nemo and SFS_CODE, varying population size, recombination rate, mutation rate, and the number of loci. I also reproduced simulations from previous studies, benchmarked QTLs and coalescent tree recording techniques. SimBit was most often the highest performing program with the only notable exception of SLiM outperforming SimBit in scenarios with few loci and low genetic diversity.

摘要

SimBit 是一种通用的、高性能的正向群体遗传学模拟器。SimBit 可以模拟各种选择情景(任何选择和显性系数变化、任何上位性相互作用、任何选择情景的时空变化等)、人口统计情景(任何斑块大小、迁移率、基于繁殖力的现实人口统计学变化、硬选择与软选择、指数增长与逻辑增长、配子或合子分散等)和交配系统(克隆和自交率、雌雄同体或雌雄异体)。SimBit 还可以跟踪 QTL(具有超维表型、显式适应景观、可塑性、发育噪声等)。最后,SimBit 可以模拟具有生态关系的多个物种。SimBit 配备了一个 R 包装器,简化了从创建参数网格和相应输入、运行模拟以及收集分析输出的整个研究项目的管理。SimBit 的性能与 SLiM、Nemo 和 SFS_CODE 进行了广泛的基准测试,比较了种群大小、重组率、突变率和基因座数量。我还复制了以前研究的模拟,基准测试了 QTL 和合并树记录技术。SimBit 通常是表现最好的程序,唯一值得注意的例外是在基因座少、遗传多样性低的情况下,SLiM 优于 SimBit。

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