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The Site Frequency Spectrum for General Coalescents

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Journal Genetics
Specialty Genetics
Date 2016 Feb 18
PMID 26883445
Citations 15
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Abstract

General genealogical processes such as Λ- and Ξ-coalescents, which respectively model multiple and simultaneous mergers, have important applications in studying marine species, strong positive selection, recurrent selective sweeps, strong bottlenecks, large sample sizes, and so on. Recently, there has been significant progress in developing useful inference tools for such general models. In particular, inference methods based on the site frequency spectrum (SFS) have received noticeable attention. Here, we derive a new formula for the expected SFS for general Λ- and Ξ-coalescents, which leads to an efficient algorithm. For time-homogeneous coalescents, the runtime of our algorithm for computing the expected SFS is O(n2) where n is the sample size. This is a factor of[Formula: see text]faster than the state-of-the-art method. Furthermore, in contrast to existing methods, our method generalizes to time-inhomogeneous Λ- and Ξ-coalescents with measures that factorize as[Formula: see text] and [Formula: see text]respectively, where ζ denotes a strictly positive function of time. The runtime of our algorithm in this setting is[Formula: see text]We also obtain general theoretical results for the identifiability of the Λ measure when ζ is a constant function, as well as for the identifiability of the function ζ under a fixed Ξ measure.

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References
1.
Eldon B, Birkner M, Blath J, Freund F . Can the site-frequency spectrum distinguish exponential population growth from multiple-merger coalescents?. Genetics. 2015; 199(3):841-56. PMC: 4349076. DOI: 10.1534/genetics.114.173807. View

2.
Birkner M, Blath J, Eldon B . An ancestral recombination graph for diploid populations with skewed offspring distribution. Genetics. 2012; 193(1):255-90. PMC: 3527250. DOI: 10.1534/genetics.112.144329. View

3.
Fu Y . Statistical properties of segregating sites. Theor Popul Biol. 1995; 48(2):172-97. DOI: 10.1006/tpbi.1995.1025. View

4.
Bhaskar A, Clark A, Song Y . Distortion of genealogical properties when the sample is very large. Proc Natl Acad Sci U S A. 2014; 111(6):2385-90. PMC: 3926037. DOI: 10.1073/pnas.1322709111. View

5.
Gutenkunst R, Hernandez R, Williamson S, Bustamante C . Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. PLoS Genet. 2009; 5(10):e1000695. PMC: 2760211. DOI: 10.1371/journal.pgen.1000695. View