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Statistical Applications in Genetics and Molecular Biology

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Volume 17, Issue 3

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Non-parametric estimation of population size changes from the site frequency spectrum

Berit Lindum Waltoft
  • Corresponding author
  • Bioinformatics Research Centre, Aarhus University, C.F. Møllers allé 8, 8000 Aarhus C, Denmark, Phone: +45 87165763
  • National Centre for Register-based Research, Department of Economics and Business, Aarhus University, Fuglesangs allé 26, 8210 Aarhus V, Denmark
  • The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Asger Hobolth
Published Online: 2018-06-11 | DOI: https://doi.org/10.1515/sagmb-2017-0061

Abstract

Changes in population size is a useful quantity for understanding the evolutionary history of a species. Genetic variation within a species can be summarized by the site frequency spectrum (SFS). For a sample of size n, the SFS is a vector of length n − 1 where entry i is the number of sites where the mutant base appears i times and the ancestral base appears ni times. We present a new method, CubSFS, for estimating the changes in population size of a panmictic population from an observed SFS. First, we provide a straightforward proof for the expression of the expected site frequency spectrum depending only on the population size. Our derivation is based on an eigenvalue decomposition of the instantaneous coalescent rate matrix. Second, we solve the inverse problem of determining the changes in population size from an observed SFS. Our solution is based on a cubic spline for the population size. The cubic spline is determined by minimizing the weighted average of two terms, namely (i) the goodness of fit to the observed SFS, and (ii) a penalty term based on the smoothness of the changes. The weight is determined by cross-validation. The new method is validated on simulated demographic histories and applied on unfolded and folded SFS from 26 different human populations from the 1000 Genomes Project.

This article offers supplementary material which is provided at the end of the article.

Keywords: Coalescent theory; population size; regularization; site frequency spectrum

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About the article

Published Online: 2018-06-11


Funding Source: Lundbeck Foundation

Award identifier / Grant number: R155–2014–1724

BLW is funded by The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark. Grant number R155–2014–1724.


Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 17, Issue 3, 20170061, ISSN (Online) 1544-6115, DOI: https://doi.org/10.1515/sagmb-2017-0061.

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