Literature DB >> 10461203

Bayesian statistics in genetics: a guide for the uninitiated.

J S Shoemaker1, I S Painter, B S Weir.   

Abstract

Statistical analyses are used in many fields of genetic research. Most geneticists are taught classical statistics, which includes hypothesis testing, estimation and the construction of confidence intervals; this framework has proved more than satisfactory in many ways. What does a Bayesian framework have to offer geneticists? Its utility lies in offering a more direct approach to some questions and the incorporation of prior information. It can also provide a more straightforward interpretation of results. The utility of a Bayesian perspective, especially for complex problems, is becoming increasingly clear to the statistics community; geneticists are also finding this framework useful and are increasingly utilizing the power of this approach.

Mesh:

Year:  1999        PMID: 10461203     DOI: 10.1016/s0168-9525(99)01751-5

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  22 in total

1.  Measuring gametic disequilibrium from multilocus data.

Authors:  K L Ayres; D J Balding
Journal:  Genetics       Date:  2001-01       Impact factor: 4.562

2.  Genetic consequences of sequential founder events by an island-colonizing bird.

Authors:  Sonya M Clegg; Sandie M Degnan; Jiro Kikkawa; Craig Moritz; Arnaud Estoup; Ian P F Owens
Journal:  Proc Natl Acad Sci U S A       Date:  2002-05-28       Impact factor: 11.205

3.  Approximate Bayesian computation in population genetics.

Authors:  Mark A Beaumont; Wenyang Zhang; David J Balding
Journal:  Genetics       Date:  2002-12       Impact factor: 4.562

4.  Comparative evaluation of a new effective population size estimator based on approximate bayesian computation.

Authors:  David A Tallmon; Gordon Luikart; Mark A Beaumont
Journal:  Genetics       Date:  2004-06       Impact factor: 4.562

5.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Authors:  Aaron McKenna; Matthew Hanna; Eric Banks; Andrey Sivachenko; Kristian Cibulskis; Andrew Kernytsky; Kiran Garimella; David Altshuler; Stacey Gabriel; Mark Daly; Mark A DePristo
Journal:  Genome Res       Date:  2010-07-19       Impact factor: 9.043

Review 6.  Bayesian statistical methods for genetic association studies.

Authors:  Matthew Stephens; David J Balding
Journal:  Nat Rev Genet       Date:  2009-10       Impact factor: 53.242

7.  CORRECTIONS FOR RACIAL DISPARITIES IN LAW ENFORCEMENT.

Authors:  Christopher L Griffin; Frank A Sloan; Lindsey M Eldred
Journal:  William Mary Law Rev       Date:  2014-04

8.  Models with a porpoise.

Authors:  Rebecca L Cann
Journal:  Proc Natl Acad Sci U S A       Date:  2012-09-04       Impact factor: 11.205

9.  AntCaller: an accurate variant caller incorporating ancient DNA damage.

Authors:  Boyan Zhou; Shaoqing Wen; Lingxiang Wang; Li Jin; Hui Li; Hong Zhang
Journal:  Mol Genet Genomics       Date:  2017-08-23       Impact factor: 3.291

10.  Phylogenetic analysis of the cytochrome P450 3 (CYP3) gene family.

Authors:  Andrew G McArthur; Tove Hegelund; Rachel L Cox; John J Stegeman; Mette Liljenberg; Urban Olsson; Per Sundberg; Malin C Celander
Journal:  J Mol Evol       Date:  2003-08       Impact factor: 2.395

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