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Rapid forward-in-time simulation at the chromosome and genome level

Aberer, Andre J; Stamatakis, Alexandros

Background: In population genetics, simulation is a fundamental tool for analyzing how basic evolutionary forces such as natural selection, recombination, and mutation shape the genetic landscape of a population. Forward simulation represents the most powerful, but, at the same time, most compute-intensive approach for simulating the genetic material of a population.
Results: We introduce AnA-FiTS, a highly optimized forward simulation software, that is up to two orders of magnitude faster than current state-of-the-art software. In addition, we present a novel algorithm that further improves runtimes by up to an additional order of magnitude, for simulations where a fraction of the mutations is neutral (e.g., only 10% of mutations have an effect on fitness). Apart from simulated sequences, our tool also generates a graph structure that depicts the complete observable history of neutral mutations.
Conclusions: The substantial performance improvements allow for conducting forward simulations at the chromosome and genome level. The graph structure generated by our algorithm can give rise to novel approaches for visualizing and analyz ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000064378
Veröffentlicht am 05.03.2018
DOI: 10.1186/1471-2105-14-216
Zitationen: 10
Web of Science
Zitationen: 21
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2013
Sprache Englisch
Identifikator ISSN: 1471-2105
KITopen-ID: 1000064378
Erschienen in BMC bioinformatics
Band 14
Seiten Art. Nr.: 216
Schlagworte Population genetics, Forward-in-time simulation, Fisher-Wright model, Algorithm, Software, Natural selection
Nachgewiesen in Web of Science
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