» Articles » PMID: 20808525

Simulation of Genes and Genomes Forward in Time

Overview
Journal Curr Genomics
Date 2010 Sep 3
PMID 20808525
Citations 22
Authors
Affiliations
Soon will be listed here.
Abstract

The importance of simulation software in current and future evolutionary and genomic studies is just confirmed by the recent publication of several new simulation tools. The forward-in-time simulation strategy has, therefore, re-emerged as a complement of coalescent simulation. Additionally, more efficient coalescent algorithms, the same as new ideas about the combined use of backward and forward strategies have recently appeared. In the present work, a previous review is updated to include some new forward simulation tools. When simulating at the genome-scale the conflict between efficiency (i.e. execution speed and memory usage) and flexibility (i.e. complex modeling capabilities) emerges. This is the pivot around which simulation of evolutionary processes should improve. In addition, some effort should be made to consider the process of developing simulation tools from the point of view of the software engineering theory. Finally, some new ideas and technologies as general purpose graphic processing units are commented.

Citing Articles

A simulation study evaluating how population survival and genetic diversity in a newly established population can be affected by propagule size, extinction rates, and initial heterozygosity.

Vera-Escalona I, Brante A PeerJ. 2024; 12:e16628.

PMID: 38239294 PMC: 10795529. DOI: 10.7717/peerj.16628.


AdmixSim 2: a forward-time simulator for modeling complex population admixture.

Zhang R, Liu C, Yuan K, Ni X, Pan Y, Xu S BMC Bioinformatics. 2021; 22(1):506.

PMID: 34663213 PMC: 8522168. DOI: 10.1186/s12859-021-04415-x.


Genetic signatures of small effective population sizes and demographic declines in an endangered rattlesnake, .

Sovic M, Fries A, Martin S, Gibbs H Evol Appl. 2019; 12(4):664-678.

PMID: 30976301 PMC: 6439488. DOI: 10.1111/eva.12731.


Evolutionary Modeling in SLiM 3 for Beginners.

Haller B, Messer P Mol Biol Evol. 2018; 36(5):1101-1109.

PMID: 30590560 PMC: 6501880. DOI: 10.1093/molbev/msy237.


SLiM 3: Forward Genetic Simulations Beyond the Wright-Fisher Model.

Haller B, Messer P Mol Biol Evol. 2018; 36(3):632-637.

PMID: 30517680 PMC: 6389312. DOI: 10.1093/molbev/msy228.


References
1.
Manavski S, Valle G . CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment. BMC Bioinformatics. 2008; 9 Suppl 2:S10. PMC: 2323659. DOI: 10.1186/1471-2105-9-S2-S10. View

2.
Balloux F . EASYPOP (version 1.7): a computer program for population genetics simulations. J Hered. 2001; 92(3):301-2. DOI: 10.1093/jhered/92.3.301. View

3.
Carvajal-Rodriguez A . GENOMEPOP: a program to simulate genomes in populations. BMC Bioinformatics. 2008; 9:223. PMC: 2386491. DOI: 10.1186/1471-2105-9-223. View

4.
Lambert B, Terwilliger J, Weiss K . ForSim: a tool for exploring the genetic architecture of complex traits with controlled truth. Bioinformatics. 2008; 24(16):1821-2. PMC: 2732213. DOI: 10.1093/bioinformatics/btn317. View

5.
Hernandez R . A flexible forward simulator for populations subject to selection and demography. Bioinformatics. 2008; 24(23):2786-7. PMC: 2639268. DOI: 10.1093/bioinformatics/btn522. View