Package: BayesQTLBIC
Version: 1.0-2
Date: 2010-05-18
Title: Bayesian multi-locus QTL analysis based on the BIC criterion
Author: Rod Ball <rod.ball@scionresearch.com>
Maintainer: Rod Ball <rod.ball@scionresearch.com>
Description: R package for a non-MCMC approximate multilocus Bayesian
        model selection approach to the analysis of quantitative trait
        loci (QTL).  The method and models are described in (Ball, R.
        D. Genetics 159: 1351--1364, 2001;
        http://www.genetics.org/cgi/content/abstract/159/3/1351).  Data
        is assumed to be from a QTL mapping family with DNA markers
        genotyped along the genome. The QTL mapping problem is
        represented as a model selection problem, where each model is a
        linear regression of the trait on a selected set of marker
        values. The main function bicreg.qtl() is based on the S
        function bicreg()--- posterior probabilities for models are
        approximated from the BIC criterion, calculated for each model
        in a search of model space using leaps or regsubsets.
        Additionally, we allow for prior probabilities based on
        expected numbers of QTL per genome and options to control the
        size of models considered, and to allow for selectivly
        genotyping from the tails of the phenotypic distribution.
        Missing values are estimated by multiple imputation, and
        estimates of marker effects can be obtained conditional on
        selection or unconditional and free of selection bias.  The
        method relies on 3 approximations: (1.) QTL configuration is
        represented approximately by configurations with QTL located at
        marker positions; (2.) Posterior probabilities are given
        approximately in terms of the BIC criterion; and (3.) The
        distribution of missing marker values is approximated by
        multiple imputation, sampling from the distribution of missing
        values conditional on non-missing values. We have found these
        are good approximations provided (1.) the marker spacing is
        reasonable (less than 30cM); (2.) the sample size is 100 or
        more for fully genotyped populations; and (3.) around 10
        imputations are used and the effect of any given QTL on the
        trait is not large. Due to limits on the number of markers that
        can be considered simultaneously the method is generally
        applied separately to each chromosome or could be iteratively
        applied to sets of chromosomes using fixed sets of predictors
        from other chromsomes when analysing a given chromosome.
Depends: leaps
License: GPL (>= 2)
URL: mailto:rod.ball@scionresearch.com www.scionresearch.com/
Packaged: 2011-10-16 21:53:43 UTC; rod
Repository: CRAN
Date/Publication: 2011-10-17 05:53:53
Built: R 2.13.2; ; 2012-01-05 12:57:41 UTC; windows
