Section: Mathematical & Computational Biology
Topic: Biophysics and computational biology, Genetics/Genomics, Evolution

An efficient algorithm for estimating population history from genetic data

10.24072/pcjournal.132 - Peer Community Journal, Volume 2 (2022), article no. e32.

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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.

Published online:
DOI: 10.24072/pcjournal.132
Type: Software tool

Rogers, Alan R. 1

1 Dept. of Anthropology, University of Utah, USA
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
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Rogers, Alan R. An efficient algorithm for estimating  population history from genetic data. Peer Community Journal, Volume 2 (2022), article  no. e32. doi : 10.24072/pcjournal.132.

PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.mcb.100003

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

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