Evaluating the effects of rescaling parameters in large-scale genomic simulations

Kıratlı, Ozan
Computer simulations are widely used in many subdisciplines of biological sciences, which evolutionary biology. Large-scale genomic simulations, where several kb (kilo base) to several Mb (megabase) genomes are modeled, are being increasingly used. These simulations require high computing power. There are some methods proposed in the literature to decrease the time and memory demand of these simulations. This study is concentrated on one of those methods, where both the number of generation, and the number of individuals are decreased, and mutation rate is increased. This rescaling method is widely used in recent years. Even though it has been criticized many times, since it could change the population dynamics, there are not many studies that evaluates the effect of rescaling on population dynamics. This study demonstrates how the rescaling of the parameters could change population dynamics with a simple model, and shows that the proportion of polymorphic loci in the simulated genomes could be significantly affected.


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Alıcı, Ahmet Yetkin; Somel, Mehmet; Department of Biology (2017)
Different types of mutations occur and spread in the genome at varying rates. For instance, C->T transitions at CpG sites are the most frequent mutation in mammalian genomes. In contrast, GC-biased gene conversion causes A or T->G or C mutations to spread and fix rapidly in populations. Such fixation biases have not yet been investigated taking neighbouring sequence context into account. Using human population genomic data from the 1000 Genomes Project and comparative genomic data from other primates, possi...
Citation Formats
O. Kıratlı, “Evaluating the effects of rescaling parameters in large-scale genomic simulations,” M.S. - Master of Science, Middle East Technical University, 2016.