Occupancy spectrum distribution: application for coalescence simulation with generic mergers
Author(s) -
Arnaud Becheler,
L. Lacey Knowles
Publication year - 2020
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa090
Subject(s) - coalescent theory , coalescence (physics) , population , computer science , binary number , approximate bayesian computation , theoretical computer science , population size , algorithm , mathematical optimization , statistical physics , mathematics , biology , physics , artificial intelligence , genetics , inference , demography , arithmetic , sociology , astrobiology , gene , phylogenetic tree
As the density of sampled population increases, especially as studies incorporate aspects of the spatial landscape to study evolutionary processes, efficient simulation of genetic data under the coalescent becomes a primary challenge. Beyond the computational demands, coalescence-based simulation strategies have to be reconsidered because traditional assumptions about the dynamics of coalescing lineages within local populations may be violated (e.g. more than two daughter lineages may coalesce to a parent at low population densities). Specifically, to efficiently assign n lineages to m parents, the order relation between n and m strongly affects the relevant algorithm for the coalescent simulator (e.g. only when n<2m, it is reasonable to assume that two lineages, at most, can be assigned to the same parent). Controlling the details of the simulation model as a function of n and m is then crucial to represent accurately and efficiently the assignment process, but current implementations make it difficult to switch between different types of lineage mergers at run-time or even compile-time.
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