Literature DB >> 15280255

Estimating recombination rates using three-site likelihoods.

Jeffrey D Wall1.   

Abstract

We introduce a new method for jointly estimating crossing-over and gene conversion rates using sequence polymorphism data. The method calculates probabilities for subsets of the data consisting of three segregating sites and then forms a composite likelihood by multiplying together the probabilities of many subsets. Simulations show that this new method performs better than previously proposed methods for estimating gene conversion rates, but that all methods require large amounts of data to provide reliable estimates. While existing methods can easily estimate an "average" gene conversion rate over many loci, they cannot reliably estimate gene conversion rates for a single region of the genome.

Mesh:

Year:  2004        PMID: 15280255      PMCID: PMC1470930          DOI: 10.1534/genetics.103.025742

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  35 in total

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Journal:  Genetics       Date:  2004-05       Impact factor: 4.562

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Journal:  Genet Res       Date:  1987-12       Impact factor: 1.588

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Authors:  T Ohta; M Kimura
Journal:  Genetics       Date:  1971-08       Impact factor: 4.562

4.  The sampling distribution of linkage disequilibrium under an infinite allele model without selection.

Authors:  R R Hudson
Journal:  Genetics       Date:  1985-03       Impact factor: 4.562

5.  Properties of a neutral allele model with intragenic recombination.

Authors:  R R Hudson
Journal:  Theor Popul Biol       Date:  1983-04       Impact factor: 1.570

Review 6.  The double-strand-break repair model for recombination.

Authors:  J W Szostak; T L Orr-Weaver; R J Rothstein; F W Stahl
Journal:  Cell       Date:  1983-05       Impact factor: 41.582

7.  Statistical properties of the number of recombination events in the history of a sample of DNA sequences.

Authors:  R R Hudson; N L Kaplan
Journal:  Genetics       Date:  1985-09       Impact factor: 4.562

8.  The sampling distribution of linkage disequilibrium.

Authors:  G B Golding
Journal:  Genetics       Date:  1984-09       Impact factor: 4.562

9.  Meiotic gene conversion tract length distribution within the rosy locus of Drosophila melanogaster.

Authors:  A J Hilliker; G Harauz; A G Reaume; M Gray; S H Clark; A Chovnick
Journal:  Genetics       Date:  1994-08       Impact factor: 4.562

10.  New HLA-DPB1 alleles generated by interallelic gene conversion detected by analysis of sperm.

Authors:  G Zangenberg; M M Huang; N Arnheim; H Erlich
Journal:  Nat Genet       Date:  1995-08       Impact factor: 38.330

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  17 in total

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Authors:  Peter L Morrell; Donna M Toleno; Karen E Lundy; Michael T Clegg
Journal:  Genetics       Date:  2006-04-19       Impact factor: 4.562

2.  A composite-likelihood approach for detecting directional selection from DNA sequence data.

Authors:  Lan Zhu; Carlos D Bustamante
Journal:  Genetics       Date:  2005-05-06       Impact factor: 4.562

3.  A comparison of three estimators of the population-scaled recombination rate: accuracy and robustness.

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Journal:  Genetics       Date:  2005-06-14       Impact factor: 4.562

4.  Estimating recombination rates from single-nucleotide polymorphisms using summary statistics.

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Journal:  Genetics       Date:  2006-09-15       Impact factor: 4.562

5.  Estimating meiotic gene conversion rates from population genetic data.

Authors:  J Gay; S Myers; G McVean
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

6.  Fraction of informative recombinations: a heuristic approach to analyze recombination rates.

Authors:  J-F Lefebvre; D Labuda
Journal:  Genetics       Date:  2008-04       Impact factor: 4.562

7.  Coalescence and Linkage Disequilibrium in Facultatively Sexual Diploids.

Authors:  Matthew Hartfield; Stephen I Wright; Aneil F Agrawal
Journal:  Genetics       Date:  2018-08-10       Impact factor: 4.562

8.  A fast estimate for the population recombination rate based on regression.

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Journal:  Genetics       Date:  2013-04-15       Impact factor: 4.562

9.  Decoding cyanobacterial phylogeny and molecular evolution using an evonumeric approach.

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10.  Inference of microbial recombination rates from metagenomic data.

Authors:  Philip L F Johnson; Montgomery Slatkin
Journal:  PLoS Genet       Date:  2009-10-02       Impact factor: 5.917

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