GENOMEPOP: a program to simulate genomes in populations.
GENOMEPOP: a program to simulate genomes in populations.
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DOI：
10.1186/1471-2105-9-223
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发表时间：
2008-04-30
影响因子：
3
通讯作者：
Carvajal-Rodríguez A
中科院分区：
文献类型：
--
作者：
Carvajal-Rodríguez A
在群体生物学研究中，模拟 DNA 序列在多种情况下很有用。可以使用后向或前向策略来模拟不同进化遗传模型下的生物种群。向后模拟，也称为基于聚结的模拟，计算效率高。原因是它们是基于当前人口中幸存后代的谱系历史。相反，正向模拟的效率较低，因为模拟的是从过去到现在的整个群体。然而，合并框架施加了一些正向模拟所没有的限制。因此，人们对正向群体遗传模拟越来越感兴趣，并且最近开发了高效的新工具。当试图更好地理解不同相互作用的进化力量在 DNA 上留下的痕迹时，能够在复杂的进化模型下有效模拟大型 DNA 片段的软件工具将非常有帮助。这里我将介绍GenomePop，一个满足上述要求的正向模拟程序。通过研究密码子内重组对全局和特定位点 dN/dS 估计的影响，证明了该程序的使用。我开发了算法并编写了软件来有效地模拟、及时转发 DNA 突变的不同马尔可夫核苷酸或密码子模型。这些模型可以与密码子间和密码子内水平的重组、基于适应性的选择和复杂的人口统计场景相结合。 GenomePop 具有许多有趣的特性，可用于在复杂的进化和人口统计模型下模拟 SNP 或 DNA 序列。这些功能使其相对于其他模拟工具独一无二。即，可以在一般时间可逆（GTR）突变或具有密码子内重组、任意、用户定义、迁移模式、二倍体或单倍体模型、恒定或可变群体大小等的GTR×MG94密码子模型下进行正向模拟。它还允许在不同突变效应分布下模拟基于适应度的选择。在2等位基因模型下，它允许模拟重组热点、不同群体中不同频率的定义等。GenomePop还可以管理大型DNA片段。此外，它还具有缩放选项，可以在复杂的人口统计和进化情况下模拟大型序列和种群规模时节省计算时间。这些以及许多其他功能在其网页中有详细介绍。
There are several situations in population biology research where simulating DNA sequences is useful. Simulation of biological populations under different evolutionary genetic models can be undertaken using backward or forward strategies. Backward simulations, also called coalescent-based simulations, are computationally efficient. The reason is that they are based on the history of lineages with surviving offspring in the current population. On the contrary, forward simulations are less efficient because the entire population is simulated from past to present. However, the coalescent framework imposes some limitations that forward simulation does not. Hence, there is an increasing interest in forward population genetic simulation and efficient new tools have been developed recently. Software tools that allow efficient simulation of large DNA fragments under complex evolutionary models will be very helpful when trying to better understand the trace left on the DNA by the different interacting evolutionary forces. Here I will introduce GenomePop, a forward simulation program that fulfills the above requirements. The use of the program is demonstrated by studying the impact of intracodon recombination on global and site-specific dN/dS estimation. I have developed algorithms and written software to efficiently simulate, forward in time, different Markovian nucleotide or codon models of DNA mutation. Such models can be combined with recombination, at inter and intra codon levels, fitness-based selection and complex demographic scenarios. GenomePop has many interesting characteristics for simulating SNPs or DNA sequences under complex evolutionary and demographic models. These features make it unique with respect to other simulation tools. Namely, the possibility of forward simulation under General Time Reversible (GTR) mutation or GTR×MG94 codon models with intra-codon recombination, arbitrary, user-defined, migration patterns, diploid or haploid models, constant or variable population sizes, etc. It also allows simulation of fitness-based selection under different distributions of mutational effects. Under the 2-allele model it allows the simulation of recombination hot-spots, the definition of different frequencies in different populations, etc. GenomePop can also manage large DNA fragments. In addition, it has a scaling option to save computation time when simulating large sequences and population sizes under complex demographic and evolutionary situations. These and many other features are detailed in its web page.
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影响因子：
64.8
作者：
Frazer, Kelly A.;Ballinger, Dennis G.;Cox, David R.;Hinds, David A.;Stuve, Laura L.;Gibbs, Richard A.;Belmont, John W.;Boudreau, Andrew;Hardenbol, Paul;Leal, Suzanne M.;Pasternak, Shiran;Wheeler, David A.;Willis, Thomas D.;Yu, Fuli;Yang, Huanming;Zeng, Changqing;Gao, Yang;Hu, Haoran;Hu, Weitao;Li, Chaohua;Lin, Wei;Liu, Siqi;Pan, Hao;Tang, Xiaoli;Wang, Jian;Wang, Wei;Yu, Jun;Zhang, Bo;Zhang, Qingrun;Zhao, Hongbin;Zhao, Hui;Zhou, Jun;Gabriel, Stacey B.;Barry, Rachel;Blumenstiel, Brendan;Camargo, Amy;Defelice, Matthew;Faggart, Maura;Goyette, Mary;Gupta, Supriya;Moore, Jamie;Nguyen, Huy;Onofrio, Robert C.;Parkin, Melissa;Roy, Jessica;Stahl, Erich;Winchester, Ellen;Ziaugra, Liuda;Altshuler, David;Shen, Yan;Yao, Zhijian;Huang, Wei;Chu, Xun;He, Yungang;Jin, Li;Liu, Yangfan;Shen, Yayun;Sun, Weiwei;Wang, Haifeng;Wang, Yi;Wang, Ying;Xiong, Xiaoyan;Xu, Liang;Waye, Mary M. Y.;Tsui, Stephen K. W.;Wong, J. Tze-Fei;Galver, Luana M.;Fan, Jian-Bing;Gunderson, Kevin;Murray, Sarah S.;Oliphant, Arnold R.;Chee, Mark S.;Montpetit, Alexandre;Chagnon, Fanny;Ferretti, Vincent;Leboeuf, Martin;Olivier, Jean-Franccois;Phillips, Michael S.;Roumy, Stephanie;Sallee, Clementine;Verner, Andrei;Hudson, Thomas J.;Kwok, Pui-Yan;Cai, Dongmei;Koboldt, Daniel C.;Miller, Raymond D.;Pawlikowska, Ludmila;Taillon-Miller, Patricia;Xiao, Ming;Tsui, Lap-Chee;Mak, William;Song, You Qiang;Tam, Paul K. H.;Nakamura, Yusuke;Kawaguchi, Takahisa;Kitamoto, Takuya;Morizono, Takashi;Nagashima, Atsushi;Ohnishi, Yozo;Sekine, Akihiro;Tanaka, Toshihiro;Tsunoda, Tatsuhiko;Deloukas, Panos;Bird, Christine P.;Delgado, Marcos;Dermitzakis, Emmanouil T.;Gwilliam, Rhian;Hunt, Sarah;Morrison, Jonathan;Powell, Don;Stranger, Barbara E.;Whittaker, Pamela;Bentley, David R.;Daly, Mark J.;de Bakker, Paul I. W.;Barrett, Jeff;Chretien, Yves R.;Maller, Julian;McCarroll, Steve;Patterson, Nick;Pe'er, Itsik;Price, Alkes;Purcell, Shaun;Richter, Daniel J.;Sabeti, Pardis;Saxena, Richa;Schaffner, Stephen F.;Sham, Pak C.;Varilly, Patrick;Altshuler, David;Stein, Lincoln D.;Krishnan, Lalitha;Smith, Albert Vernon;Tello-Ruiz, Marcela K.;Thorisson, Gudmundur A.;Chakravarti, Aravinda;Chen, Peter E.;Cutler, David J.;Kashuk, Carl S.;Lin, Shin;Abecasis, Goncalo R.;Guan, Weihua;Li, Yun;Munro, Heather M.;Qin, Zhaohui Steve;Thomas, Daryl J.;McVean, Gilean;Auton, Adam;Bottolo, Leonardo;Cardin, Niall;Eyheramendy, Susana;Freeman, Colin;Marchini, Jonathan;Myers, Simon;Spencer, Chris;Stephens, Matthew;Donnelly, Peter;Cardon, Lon R.;Clarke, Geraldine;Evans, David M.;Morris, Andrew P.;Weir, Bruce S.;Tsunoda, Tatsuhiko;Johnson, Todd A.;Mullikin, James C.;Sherry, Stephen T.;Feolo, Michael;Skol, Andrew
通讯作者：
Skol, Andrew
影响因子：
1.9
作者：
Bahlo, M;Griffiths, RC
通讯作者：
Griffiths, RC
影响因子：
7
作者：
Greenawalt, DM;Cui, XF;Li, HH
通讯作者：
Li, HH
DOI：
10.1073/pnas.081068098
发表时间：
2001-04-10
影响因子：
11.1
作者：
Beerli, P;Felsenstein, J
通讯作者：
Felsenstein, J
影响因子：
1.4
作者：
Krone, SM;Neuhauser, C
通讯作者：
Neuhauser, C