Literature DB >> 18417488

Forward-time simulations of non-random mating populations using simuPOP.

Bo Peng1, Christopher I Amos.   

Abstract

UNLABELLED: Computer simulations play an important role in studies of non-random mating populations. Because of implementation difficulties, only very limited types of non-random mating schemes are provided in the currently available simulation programs. Starting with version 0.8.5, simuPOP provides a few mating schemes that can be used to simulate arbitrary non-random mating models. This article describes the concepts and methods behind these mating schemes and demonstrates their uses in a few examples, including partial self-mating, positive assortative mating, non-random outbreeding, and simulation of overlapping generations in age-structured populations. AVAILABILITY: simuPOP is freely available at http://simupop.sourceforge.net, distributed under a GPL license. Cited examples are in the doc/cookbook directory of a simuPOP distribution.

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Mesh:

Year:  2008        PMID: 18417488      PMCID: PMC2691961          DOI: 10.1093/bioinformatics/btn179

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  EASYPOP (version 1.7): a computer program for population genetics simulations.

Authors:  F Balloux
Journal:  J Hered       Date:  2001 May-Jun       Impact factor: 2.645

2.  Effective size of nonrandom mating populations.

Authors:  A Caballero; W G Hill
Journal:  Genetics       Date:  1992-04       Impact factor: 4.562

3.  simuPOP: a forward-time population genetics simulation environment.

Authors:  Bo Peng; Marek Kimmel
Journal:  Bioinformatics       Date:  2005-07-14       Impact factor: 6.937

4.  Social structure of pilot whales revealed by analytical DNA profiling.

Authors:  B Amos; C Schlötterer; D Tautz
Journal:  Science       Date:  1993-04-30       Impact factor: 47.728

  4 in total
  23 in total

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2.  An efficient gene-gene interaction test for genome-wide association studies in trio families.

Authors:  Pei-Yuan Sung; Yi-Ting Wang; Ya-Wen Yu; Ren-Hua Chung
Journal:  Bioinformatics       Date:  2016-02-11       Impact factor: 6.937

3.  A C++ template library for efficient forward-time population genetic simulation of large populations.

Authors:  Kevin R Thornton
Journal:  Genetics       Date:  2014-06-20       Impact factor: 4.562

4.  A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods.

Authors:  Jason H Moore; Maksim Shestov; Peter Schmitt; Randal S Olson
Journal:  Pac Symp Biocomput       Date:  2018

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Journal:  Genetics       Date:  2022-03-03       Impact factor: 4.562

6.  Genomic epidemiological models describe pathogen evolution across fitness valleys.

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Journal:  Sci Adv       Date:  2022-07-13       Impact factor: 14.957

7.  Forward-time simulation of realistic samples for genome-wide association studies.

Authors:  Bo Peng; Christopher I Amos
Journal:  BMC Bioinformatics       Date:  2010-09-01       Impact factor: 3.169

8.  Genetic homogeneity in the face of morphological heterogeneity in the harbor porpoise from the Black Sea and adjacent waters (Phocoena phocoena relicta).

Authors:  Yacine Ben Chehida; Julie Thumloup; Karina Vishnyakova; Pavel Gol'din; Michael C Fontaine
Journal:  Heredity (Edinb)       Date:  2019-11-26       Impact factor: 3.821

9.  Identity-by-descent-based phasing and imputation in founder populations using graphical models.

Authors:  Kimmo Palin; Harry Campbell; Alan F Wright; James F Wilson; Richard Durbin
Journal:  Genet Epidemiol       Date:  2011-10-17       Impact factor: 2.135

Review 10.  A survey of genetic simulation software for population and epidemiological studies.

Authors:  Youfang Liu; Georgios Athanasiadis; Michael E Weale
Journal:  Hum Genomics       Date:  2008-09       Impact factor: 4.639

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