Literature DB >> 18046760

Model selection and Bayesian methods in statistical genetics: summary of group 11 contributions to Genetic Analysis Workshop 15.

Michael D Swartz1, Duncan C Thomas, E Warwick Daw, Kees Albers, Jac C Charlesworth, Thomas C Dyer, Brooke L Fridley, Manika Govil, Peter Kraft, Soonil Kwon, Mark W Logue, Cheongeun Oh, Roger Pique-Regi, Laura Saba, Fredrick R Schumacher, Hae-Won Uh.   

Abstract

The research presented in group 11 of the Genetic Analysis Workshop 15 (GAW15) falls into two major themes: Model selection approaches for gene mapping (both Bayesian and Frequentist); and other Bayesian methods. These methods either allow relaxation of some of the common assumptions, such as mode of inheritance, for studying complicated genetic systems, or allow incorporation of additional information into the model. Over half of the groups applied model selection methods on all three data sets, using models in which genetic markers were used as predictors for linkage, phenotype expression, or transmission to an affected offspring. Most groups employed variations of Stochastic Search Variable Selection as the model selection method of choice. A brief review of this class of methods is given in this summary paper, followed by highlights of other methods and overall summaries of each contribution to the GAW15 presentation group 11. These group contributions exhibit the value of framing genetic problems in terms of model selection, and highlight the impact of variable selection for gene mapping. (c) 2007 Wiley-Liss, Inc.

Mesh:

Year:  2007        PMID: 18046760     DOI: 10.1002/gepi.20285

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  5 in total

1.  Identification of significant genes in genomics using Bayesian variable selection methods.

Authors:  Eugene Lin; Lung-Cheng Huang
Journal:  Adv Appl Bioinform Chem       Date:  2008-07-01

2.  Finding factors influencing risk: comparing Bayesian stochastic search and standard variable selection methods applied to logistic regression models of cases and controls.

Authors:  Michael D Swartz; Robert K Yu; Sanjay Shete
Journal:  Stat Med       Date:  2008-12-20       Impact factor: 2.373

3.  Air toxics and birth defects: a Bayesian hierarchical approach to evaluate multiple pollutants and spina bifida.

Authors:  Michael D Swartz; Yi Cai; Wenyaw Chan; Elaine Symanski; Laura E Mitchell; Heather E Danysh; Peter H Langlois; Philip J Lupo
Journal:  Environ Health       Date:  2015-02-09       Impact factor: 5.984

4.  Obstructive sleep apnoea, positive airway pressure treatment and postoperative delirium: protocol for a retrospective observational study.

Authors:  Christopher R King; Krisztina E Escallier; Yo-El S Ju; Nan Lin; Ben Julian Palanca; Sherry Lynn McKinnon; Michael Simon Avidan
Journal:  BMJ Open       Date:  2019-08-26       Impact factor: 2.692

5.  Investigating multiple candidate genes and nutrients in the folate metabolism pathway to detect genetic and nutritional risk factors for lung cancer.

Authors:  Michael D Swartz; Christine B Peterson; Philip J Lupo; Xifeng Wu; Michele R Forman; Margaret R Spitz; Ladia M Hernandez; Marina Vannucci; Sanjay Shete
Journal:  PLoS One       Date:  2013-01-23       Impact factor: 3.240

  5 in total

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