A flexible forward simulator for populations subject to selection and demography
This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic...
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| Published in | Bioinformatics Vol. 24; no. 23; pp. 2786 - 2787 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Oxford University Press
01.12.2008
Oxford Publishing Limited (England) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net. |
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| AbstractList | This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent).UNLABELLEDThis article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent).The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit.AVAILABILITYThe source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net. This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net. This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent).Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit.Contact: rhernandez super(c)hicago.eduSupplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net. This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program ( SFS_CODE ) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net , and a web server ( http://cbsuapps.tc.cornell.edu/sfscode.aspx ) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net . This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). Availability: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. Contact: rhernandez@uchicago.edu Supplementary information: An extensive user's manual, perfor-mance statistics, and comparisons of patterns of genetic variation generated by SFS_CODE to theoretical expectations under various non-stationary demographic histories and models of natural selection are available on the project website: http://sfscode.sourceforge.net. This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit. |
| Author | Hernandez, Ryan D. |
| AuthorAffiliation | Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA |
| AuthorAffiliation_xml | – name: Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14850, USA |
| Author_xml | – sequence: 1 givenname: Ryan D. surname: Hernandez fullname: Hernandez, Ryan D. |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20875957$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/18842601$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1145/3828.3835 10.1093/bioinformatics/bti584 10.1093/bioinformatics/btl415 10.1534/genetics.107.085332 10.1007/BF01731581 10.1071/BI9570484 10.1093/molbev/msm108 10.1016/B978-1-4832-3211-9.50009-7 10.1093/bioinformatics/18.2.337 10.1371/journal.pgen.1000083 10.1186/1471-2105-9-223 10.1073/pnas.0404142101 |
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| Copyright | The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org 2008 2009 INIST-CNRS The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org |
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| References | Hwang (2023020212234037600_B8) 2004; 101 Sleator (2023020212234037600_B13) 1985; 32 Hey (2023020212234037600_B6) 2004 Hudson (2023020212234037600_B7) 2002; 18 Kimura (2023020212234037600_B10) 1980; 16 Peng (2023020212234037600_B12) 2005; 21 Carvajal-Rodríguez (2023020212234037600_B2) 2008; 9 Fraser (2023020212234037600_B3) 1957; 10 Jukes (2023020212234037600_B9) 1969 Guillaume (2023020212234037600_B4) 2006; 22 Padhukasahasram (2023020212234037600_B11) 2008; 178 Boyko (2023020212234037600_B1) 2008; 4 Hernandez (2023020212234037600_B5) 2007; 24 7463489 - J Mol Evol. 1980 Dec;16(2):111-20 17545186 - Mol Biol Evol. 2007 Aug;24(8):1792-800 11847089 - Bioinformatics. 2002 Feb;18(2):337-8 15292512 - Proc Natl Acad Sci U S A. 2004 Sep 28;101(39):13994-4001 18430959 - Genetics. 2008 Apr;178(4):2417-27 18516229 - PLoS Genet. 2008 May;4(5):e1000083 16020469 - Bioinformatics. 2005 Sep 15;21(18):3686-7 16882649 - Bioinformatics. 2006 Oct 15;22(20):2556-7 18447924 - BMC Bioinformatics. 2008;9:223 |
| References_xml | – volume: 32 start-page: 652 year: 1985 ident: 2023020212234037600_B13 article-title: Self-adjusting binary search trees publication-title: J. ACM doi: 10.1145/3828.3835 – volume: 21 start-page: 3686 year: 2005 ident: 2023020212234037600_B12 article-title: simuPOP: a forward-time population genetics simulation environment publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti584 – volume: 22 start-page: 2556 year: 2006 ident: 2023020212234037600_B4 article-title: Nemo: an evolutionary and population genetics programming framework publication-title: Bioinformatics doi: 10.1093/bioinformatics/btl415 – year: 2004 ident: 2023020212234037600_B6 – volume: 178 start-page: 2417 year: 2008 ident: 2023020212234037600_B11 article-title: Exploring population genetic models with recombination using efficient forward-time simulations publication-title: Genetics doi: 10.1534/genetics.107.085332 – volume: 16 start-page: 111 year: 1980 ident: 2023020212234037600_B10 article-title: A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences publication-title: J. Mol. Evol. doi: 10.1007/BF01731581 – volume: 10 start-page: 484 year: 1957 ident: 2023020212234037600_B3 article-title: Simulating of genetic systems by automatic digital computers publication-title: Aust. J. Biol. Sci. doi: 10.1071/BI9570484 – volume: 24 start-page: 1792 year: 2007 ident: 2023020212234037600_B5 article-title: Context dependence, ancestral misidentification, and spurious signatures of natural selection publication-title: Mol. Biol. Evol. doi: 10.1093/molbev/msm108 – start-page: 21 volume-title: Mammalian Protein Metabolism year: 1969 ident: 2023020212234037600_B9 article-title: Evolution of protein molecules doi: 10.1016/B978-1-4832-3211-9.50009-7 – volume: 18 start-page: 337 year: 2002 ident: 2023020212234037600_B7 article-title: Generating samples under a Wright-Fisher neutral model of genetic variation publication-title: Bioinformatics doi: 10.1093/bioinformatics/18.2.337 – volume: 4 start-page: e1000083 year: 2008 ident: 2023020212234037600_B1 article-title: Assessing the evolutionary impact of amino acid mutations in the human genome publication-title: PLoS Genet doi: 10.1371/journal.pgen.1000083 – volume: 9 start-page: 223 year: 2008 ident: 2023020212234037600_B2 article-title: Genomepop: a program to simulate genomes in populations publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-223 – volume: 101 start-page: 13994 year: 2004 ident: 2023020212234037600_B8 article-title: Bayesian Markov chain Monte Carlo sequence analysis reveals varying neutral substitution patterns in mammalian evolution publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0404142101 – reference: 16882649 - Bioinformatics. 2006 Oct 15;22(20):2556-7 – reference: 11847089 - Bioinformatics. 2002 Feb;18(2):337-8 – reference: 17545186 - Mol Biol Evol. 2007 Aug;24(8):1792-800 – reference: 18430959 - Genetics. 2008 Apr;178(4):2417-27 – reference: 18447924 - BMC Bioinformatics. 2008;9:223 – reference: 18516229 - PLoS Genet. 2008 May;4(5):e1000083 – reference: 7463489 - J Mol Evol. 1980 Dec;16(2):111-20 – reference: 16020469 - Bioinformatics. 2005 Sep 15;21(18):3686-7 – reference: 15292512 - Proc Natl Acad Sci U S A. 2004 Sep 28;101(39):13994-4001 |
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| Snippet | This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic... |
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| SubjectTerms | Algorithms Applications Note Biological and medical sciences Biological Evolution Computer Simulation Demography Fundamental and applied biological sciences. Psychology General aspects Genetic diversity Genetics, Population Genome, Human Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Genetic Population - genetics Selection, Genetic Software |
| Title | A flexible forward simulator for populations subject to selection and demography |
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