GeneRecon 1.2

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GeneRecon 1.2 Ranking & Summary

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User Review: 0 (0 times)
File size: 0.18 MB
Platform: Any Platform
License: GPL (GNU General Public License)
Price:
Downloads: 1299
Date added: 2006-04-03
Publisher: Thomas Mailund

GeneRecon 1.2 description

GeneRecon is a software package for linkage disequilibrium mapping using coalescent theory. GeneRecon project is based on a Bayesian Markov-chain Monte Carlo (MCMC) method for fine-scale linkage-disequilibrium gene mapping using high-density marker maps.
GeneRecon explicitly models the genealogy of a sample of the case chromosomes in the vicinity of a disease locus. Given case and control data in the form of genotype or haplotype information, it estimates a number of parameters, most importantly, the disease position.
GeneRecon is written in C++ and Guile Scheme and is available as source code (under the GNU General Public License, GPL) and as binary versions as Linux RPM files.
The source code has been successfully compiled on various Linux and UNIX systems, under OS X and under Windows with Cygwin.
As I have only limited access to architectures other than Linux, it is not possible for me to make binary distributions for other platforms, but if anyone is willing to build the distributions I will be more than happy to put them on this site.
Installation:
$ tar zxf generecon-version.tar.gz
$ cd generecon-version
$ ./configure
$ make
$ make check
$ make install
Usage:
GeneRecon is started from the command-line; the input data and parameters for the analysis are described in one or more configuration scripts written in the Scheme programming language. Starting GeneRecon with the configuration script input.scm is done as:
$ generecon input.scm
Run generecon --help to get a complete list of command-line options accepted by GeneRecon, or see Getting Started for a quick guide to running GeneRecon.
Enhancements:
- This version fixes an incorrect prior on the coalescent tree that resulted in very long convergence times.
- The fix greatly improves both accuracy and number of iterations needed for accurate mapping.

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