Package: MISA
Type: Package
Title: Bayesian Model Search and Multilevel Inference for SNP
        Association Studies
Author: Melanie Wilson <maw27@stat.duke.edu>
Maintainer: Gary Lipton <gl37@stat.duke.edu>
Description: The functions in this package focus on intermediate
        throughput case-control association studies, where the outcome
        of interest is often a binary disease state and where the
        genetic markers have been chosen to capture variation in a set
        of related genes, such as those involved in a specific
        biochemical pathway. Given this data, we are interested in
        addressing two questions: "To what extent does the data support
        an overall association between the pathway and outcome of
        interest?" and "Which markers or genes are most likely to be
        driving this association?" To address both of these
        questions,this package performs a Bayesian model search
        technique that utilizes Evolutionary Monte Carlo and searches
        over models including main effects of all genetic markers and
        marker-specific genetic effects in a computationally efficient
        manner.  The package incorporates functions that perform a
        marginal screen on the genetic markers, summarize the output of
        the model search algorithm, including image plots of the models
        with the highest posterior probability, marginal summaries of
        SNP and gene inclusion probabilities and Bayes Factors, and
        global summaries of the posterior probability and Bayes Factor
        giving evidence of an association in the set of SNPs of
        interest.
Version: 2.11.1-1.0.1
License: Unlimited
Depends: R (>= 2.10), coda
Suggests: tcltk
Packaged: 2012-07-23 09:31:19 UTC; ripley
Repository: CRAN
Date/Publication: 2012-07-23 10:35:31
