Literature DB >> 17947444

Sequence-level population simulations over large genomic regions.

Clive J Hoggart1, Marc Chadeau-Hyam, Taane G Clark, Riccardo Lampariello, John C Whittaker, Maria De Iorio, David J Balding.   

Abstract

Simulation is an invaluable tool for investigating the effects of various population genetics modeling assumptions on resulting patterns of genetic diversity, and for assessing the performance of statistical techniques, for example those designed to detect and measure the genomic effects of selection. It is also used to investigate the effectiveness of various design options for genetic association studies. Backward-in-time simulation methods are computationally efficient and have become widely used since their introduction in the 1980s. The forward-in-time approach has substantial advantages in terms of accuracy and modeling flexibility, but at greater computational cost. We have developed flexible and efficient simulation software and a rescaling technique to aid computational efficiency that together allow the simulation of sequence-level data over large genomic regions in entire diploid populations under various scenarios for demography, mutation, selection, and recombination, the latter including hotspots and gene conversion. Our forward evolution of genomic regions (FREGENE) software is freely available from www.ebi.ac.uk/projects/BARGEN together with an ancillary program to generate phenotype labels, either binary or quantitative. In this article we discuss limitations of coalescent-based simulation, introduce the rescaling technique that makes large-scale forward-in-time simulation feasible, and demonstrate the utility of various features of FREGENE, many not previously available.

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Year:  2007        PMID: 17947444      PMCID: PMC2147962          DOI: 10.1534/genetics.106.069088

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  21 in total

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2.  SelSim: a program to simulate population genetic data with natural selection and recombination.

Authors:  Chris C A Spencer; Graham Coop
Journal:  Bioinformatics       Date:  2004-07-22       Impact factor: 6.937

3.  A fine-scale map of recombination rates and hotspots across the human genome.

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Journal:  Science       Date:  2005-10-14       Impact factor: 47.728

4.  Genomic regions exhibiting positive selection identified from dense genotype data.

Authors:  Christopher S Carlson; Daryl J Thomas; Michael A Eberle; Johanna E Swanson; Robert J Livingston; Mark J Rieder; Deborah A Nickerson
Journal:  Genome Res       Date:  2005-11       Impact factor: 9.043

5.  Genomic scans for selective sweeps using SNP data.

Authors:  Rasmus Nielsen; Scott Williamson; Yuseob Kim; Melissa J Hubisz; Andrew G Clark; Carlos Bustamante
Journal:  Genome Res       Date:  2005-11       Impact factor: 9.043

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

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

7.  Simulations provide support for the common disease-common variant hypothesis.

Authors:  Bo Peng; Marek Kimmel
Journal:  Genetics       Date:  2006-12-06       Impact factor: 4.562

8.  Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Authors:  F Tajima
Journal:  Genetics       Date:  1989-11       Impact factor: 4.562

9.  Properties of a neutral allele model with intragenic recombination.

Authors:  R R Hudson
Journal:  Theor Popul Biol       Date:  1983-04       Impact factor: 1.570

10.  The fine-scale structure of recombination rate variation in the human genome.

Authors:  Gilean A T McVean; Simon R Myers; Sarah Hunt; Panos Deloukas; David R Bentley; Peter Donnelly
Journal:  Science       Date:  2004-04-23       Impact factor: 47.728

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  61 in total

1.  Evolutionary origins of transcription factor binding site clusters.

Authors:  Xin He; Thyago S P C Duque; Saurabh Sinha
Journal:  Mol Biol Evol       Date:  2011-11-10       Impact factor: 16.240

Review 2.  Computer simulations: tools for population and evolutionary genetics.

Authors:  Sean Hoban; Giorgio Bertorelle; Oscar E Gaggiotti
Journal:  Nat Rev Genet       Date:  2012-01-10       Impact factor: 53.242

Review 3.  An overview of population genetic data simulation.

Authors:  Xiguo Yuan; David J Miller; Junying Zhang; David Herrington; Yue Wang
Journal:  J Comput Biol       Date:  2011-12-09       Impact factor: 1.479

4.  Searching for footprints of positive selection in whole-genome SNP data from nonequilibrium populations.

Authors:  Pavlos Pavlidis; Jeffrey D Jensen; Wolfgang Stephan
Journal:  Genetics       Date:  2010-04-20       Impact factor: 4.562

5.  Accurate prediction of genetic values for complex traits by whole-genome resequencing.

Authors:  Theo Meuwissen; Mike Goddard
Journal:  Genetics       Date:  2010-03-22       Impact factor: 4.562

6.  Detecting directional selection in the presence of recent admixture in African-Americans.

Authors:  Kirk E Lohmueller; Carlos D Bustamante; Andrew G Clark
Journal:  Genetics       Date:  2010-12-31       Impact factor: 4.562

7.  GCTA: a tool for genome-wide complex trait analysis.

Authors:  Jian Yang; S Hong Lee; Michael E Goddard; Peter M Visscher
Journal:  Am J Hum Genet       Date:  2010-12-17       Impact factor: 11.025

8.  Simulating sequences of the human genome with rare variants.

Authors:  Bo Peng; Xiaoming Liu
Journal:  Hum Hered       Date:  2011-01-06       Impact factor: 0.444

Review 9.  Reconciling the analysis of IBD and IBS in complex trait studies.

Authors:  Joseph E Powell; Peter M Visscher; Michael E Goddard
Journal:  Nat Rev Genet       Date:  2010-09-28       Impact factor: 53.242

10.  Efficient whole-genome association mapping using local phylogenies for unphased genotype data.

Authors:  Zhihong Ding; Thomas Mailund; Yun S Song
Journal:  Bioinformatics       Date:  2008-07-30       Impact factor: 6.937

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