Literature DB >> 17449894

Comparisons of site- and haplotype-frequency methods for detecting positive selection.

Kai Zeng1, Shuhei Mano, Suhua Shi, Chung-I Wu.   

Abstract

In this report, we compare the differences between various site- and haplotype-frequency tests in their power to detect positive selection by doing computer simulations. Our results are the following. 1) Although haplotype-frequency tests that are conditional on the number of haplotypes (K) were developed for nonrecombining haplotypes, these tests are insensitive to recombination. Such tests, including the Ewens-Watterson (EW) test, can therefore be applied to recombining haplotypes. 2) Tests conditional on the number of segregating sites (S) become overly conservative in the presence of recombination. 3) The EW test is usually the most powerful test during the sweep phase, especially when the local recombination rate is high. 4) The "extended haplotype homozygosity" test relies heavily on the prior knowledge of the target of selection. With that knowledge, it is the most powerful test, whereas in the absence of this prior information, the test has little power. We also study the sensitivities of the haplotype-frequency tests to background selection and various demographic forces. We find that these tests are sensitive to some forces other than positive selection. To alleviate the problem of low specificity, compound tests, such as the DH test (Zeng et al. 2006), may be a solution. In the companion paper (Zeng K, Shi S, Wu C-I, in preparation), we use the EW test to devise 2 compound tests, which are more powerful in detecting positive selection than DH, but are also relatively insensitive to demography.

Entities:  

Mesh:

Year:  2007        PMID: 17449894     DOI: 10.1093/molbev/msm078

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  30 in total

1.  Methods for human demographic inference using haplotype patterns from genomewide single-nucleotide polymorphism data.

Authors:  Kirk E Lohmueller; Carlos D Bustamante; Andrew G Clark
Journal:  Genetics       Date:  2009-03-02       Impact factor: 4.562

2.  The relationship between homozygosity and the frequency of the most frequent allele.

Authors:  Noah A Rosenberg; Mattias Jakobsson
Journal:  Genetics       Date:  2008-08-09       Impact factor: 4.562

3.  An investigation of the statistical power of neutrality tests based on comparative and population genetic data.

Authors:  Weiwei Zhai; Rasmus Nielsen; Montgomery Slatkin
Journal:  Mol Biol Evol       Date:  2008-10-14       Impact factor: 16.240

4.  The spread of a transposon insertion in Rec8 is associated with obligate asexuality in Daphnia.

Authors:  Brian D Eads; Dai Tsuchiya; Justen Andrews; Michael Lynch; Miriam E Zolan
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-03       Impact factor: 11.205

5.  Scanning for the signatures of positive selection for human-specific insertions and deletions.

Authors:  Chun-Hsi Chen; Trees-Juen Chuang; Ben-Yang Liao; Feng-Chi Chen
Journal:  Genome Biol Evol       Date:  2009-10-20       Impact factor: 3.416

6.  Evidence for positive selection in the gene fruitless in Anastrepha fruit flies.

Authors:  Iderval S Sobrinho; Reinaldo A de Brito
Journal:  BMC Evol Biol       Date:  2010-09-24       Impact factor: 3.260

7.  An evolutionary framework for association testing in resequencing studies.

Authors:  C Ryan King; Paul J Rathouz; Dan L Nicolae
Journal:  PLoS Genet       Date:  2010-11-11       Impact factor: 5.917

8.  Adaptive evolution of newly emerged micro-RNA genes in Drosophila.

Authors:  Jian Lu; Yonggui Fu; Supriya Kumar; Yang Shen; Kai Zeng; Anlong Xu; Richard Carthew; Chung-I Wu
Journal:  Mol Biol Evol       Date:  2008-02-22       Impact factor: 16.240

9.  The evolution of amastin surface glycoproteins in trypanosomatid parasites.

Authors:  Andrew P Jackson
Journal:  Mol Biol Evol       Date:  2010-01       Impact factor: 16.240

10.  Measuring the sensitivity of single-locus "neutrality tests" using a direct perturbation approach.

Authors:  Daniel Garrigan; Richard Lewontin; John Wakeley
Journal:  Mol Biol Evol       Date:  2010-01       Impact factor: 16.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.