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An efficient algorithm for estimating population history from genetic datause asterix (*) to get italics
Alan R. RogersPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
2021
<p style="text-align: justify;">The Legofit statistical package uses genetic data to estimate parameters describing population history. Previous versions used computer simulations to estimate probabilities, an approach that limited both speed and accuracy. This article describes a new deterministic algorithm, which makes Legofit faster and more accurate. The speed of this algorithm declines as model complexity increases. With very complex models, the deterministic algorithm is slower than the stochastic one. In an application to simulated data sets, the estimates produced by the deterministic and stochastic algorithms were essentially identical. Reanalysis of a human data set replicated the findings of a previous study and provided increased support for the hypotheses that (a) early modern humans contributed genes to Neanderthals, and (b) a “superarchaic” population (which separated from all other humans early in the Pleistocene) was either large or deeply subdivided.</p>
https:/doi.org/10.17605/OSF.IO/74BJFYou should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
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population genetics, statistical inference, Markov chains, combinatorics, population history
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Combinatorics, Genetics and population Genetics
No need for them to be recommenders of PCI Math Comp Biol. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
e.g. John Doe [john@doe.com]
2021-01-26 20:04:35
Matteo Fumagalli