×

Probability that a sequence is lost without trace under the neutral Wright-Fisher model with recombination. (English) Zbl 1334.60139

Summary: I describe an approximate formula for calculating the short-term probability of loss of a sequence under the neutral Wright-Fisher model with recombination. I also present an upper and lower bound for this probability. Exact analytical calculation of this quantity is difficult and computationally expensive because the number of different ways in which a sequence can be lost grows very large in the presence of recombination. Simulations indicate that the probabilities obtained using my approximation are always comparable to the true expectations provided that the number of generations remains small. These results are useful in the context of an algorithm that we recently developed for simulating Wright-Fisher populations forward in time.

MSC:

60J05 Discrete-time Markov processes on general state spaces
60J22 Computational methods in Markov chains
65C40 Numerical analysis or methods applied to Markov chains

Software:

simuPOP

References:

[1] Durret R (2002) Probability models for DNA sequence evolution. Springer, New York · Zbl 0991.92021 · doi:10.1007/978-1-4757-6285-3
[2] Fisher RA (1930) The genetical theory of natural selection. Clarendon, Oxford · JFM 56.1106.13
[3] Griffiths RC (1981) Neutral two-locus multiple allele models with recombination. Theor Popul Biol 19:169-186 · Zbl 0512.92012 · doi:10.1016/0040-5809(81)90016-2
[4] Hein J, Schierup MH, Wiuf C (2005) Gene genealogies, variation and evolution: a primer in coalescent theory. Oxford University Press · Zbl 1113.92048
[5] Hernandez RD (2008) A flexible forward simulator for populations subject to selection and demography. Bioinformatics 24:2786-2787 · doi:10.1093/bioinformatics/btn522
[6] Hoggart CJ, Chadeau-Hyam M, Clark TG, Lampariello R, Whittaker JC, De lorio M, Balding DJ (2007) Sequence-level population simulations over large genomic regions. Genetics 177:1725-1731 · doi:10.1534/genetics.106.069088
[7] Hudson RR (1983) Properties of a neutral allele model with intragenic recombination. Theor Popul Biol 23:183-201 · Zbl 0505.62090 · doi:10.1016/0040-5809(83)90013-8
[8] Kimmel M, Peng B (2005) simuPOP: a forward-time population genetics simulation environment. Bioinformatics 21:3686-3687 · doi:10.1093/bioinformatics/bti584
[9] Kimura M, Ohta T (2001) Theoretical aspects of population genetics. Princeton University Press, Princeton, NJ · Zbl 0239.92002
[10] Kingman JFC (1982) On the genealogy of large populations. Stoch Proc Appl 13:235-248 · Zbl 0491.60076 · doi:10.1016/0304-4149(82)90011-4
[11] Padhukasahasram B, Marjoram P, Wall JD, Bustamante CD, Nordborg M (2008) Exploring population genetic models with recombination using efficient forward-time simulations. Genetics 178:2417-2427 · doi:10.1534/genetics.107.085332
[12] Wakeley J (2008) Coalescent theory. Ben Roberts, Greenwood Village · Zbl 1366.92001
[13] Wright S (1931) Evolution in Mendelian populations. Genetics 16:97-159
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.