Literature DB >> 12427459

On the minimum number of topologies explaining a sample of DNA sequences.

Carsten Wiuf1.   

Abstract

In this article I derive an alternative algorithm to Hudson and Kaplan's (Genetics 111, 147-165) algorithm that gives a lower bound to the number of recombination events in a sample's history. It is shown that the number, T(M), found by the algorithm is the least number of topologies required to explain a set of DNA sequences sampled under the infinite-site assumption. Let Tao = (T(1),...,T(r)) be a list of topologies compatible with the sequences, i.e., T(k) is compatible with an interval, I(k), of sites in the alignment. A characterization of all lists having T(M) topologies is given and it is shown that T(M) relates to specific patterns in the alignment, here called chain series. Further, a number of theorems relating general lists of topologies to the number T(M) is presented. The results are discussed in relation to the true minimum number of recombination events required to explain an alignment. Copyright 2002 Elsevier Science (USA)

Mesh:

Substances:

Year:  2002        PMID: 12427459     DOI: 10.1016/s0040-5809(02)00004-7

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  5 in total

1.  Inference on recombination and block structure using unphased data.

Authors:  Carsten Wiuf
Journal:  Genetics       Date:  2004-01       Impact factor: 4.562

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

Authors:  Kao Lin; Andreas Futschik; Haipeng Li
Journal:  Genetics       Date:  2013-04-15       Impact factor: 4.562

3.  Improved Versions of Common Estimators of the Recombination Rate.

Authors:  Kerstin Gärtner; Andreas Futschik
Journal:  J Comput Biol       Date:  2016-07-13       Impact factor: 1.479

4.  Predicting the Landscape of Recombination Using Deep Learning.

Authors:  Jeffrey R Adrion; Jared G Galloway; Andrew D Kern
Journal:  Mol Biol Evol       Date:  2020-06-01       Impact factor: 16.240

5.  LDJump: Estimating variable recombination rates from population genetic data.

Authors:  Philipp Hermann; Angelika Heissl; Irene Tiemann-Boege; Andreas Futschik
Journal:  Mol Ecol Resour       Date:  2019-04-04       Impact factor: 7.090

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.