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Clotho: addressing the scalability of forward time population genetic simulation

BACKGROUND: Forward Time Population Genetic Simulations offer a flexible framework for modeling the various evolutionary processes occurring in nature. Often this model expressibility is countered by an increased memory usage or computational overhead. With the complexity of simulation scenarios con...

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Detalles Bibliográficos
Autores principales: Putnam, Patrick P., Wilsey, Philip A., Zhang, Ge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4460757/
https://www.ncbi.nlm.nih.gov/pubmed/26056047
http://dx.doi.org/10.1186/s12859-015-0631-z
Descripción
Sumario:BACKGROUND: Forward Time Population Genetic Simulations offer a flexible framework for modeling the various evolutionary processes occurring in nature. Often this model expressibility is countered by an increased memory usage or computational overhead. With the complexity of simulation scenarios continuing to increase, addressing the scalability of the underlying simulation framework is a growing consideration. RESULTS: We propose a general method for representing in silico genetic sequences using implicit data structures. We provide a generalized implementation as a C++ template library called Clotho. We compare the performance and scalability of our approach with those taken in other simulation frameworks, namely: FWDPP and simuPOP. CONCLUSIONS: We show that this technique offers a 4x reduction in memory utilization. Additionally, with larger scale simulation scenarios we are able to offer a speedup of 6x - 46x.