Downloads
 Release 2.2
 - Windows (GUI)
 - Linux
 Release 2.14
 - Windows (GUI)
 - Mac OS X (GUI)
 - Linux (threaded)
 - Linux (non-threaded)
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DMLE+ LINKAGE DISEQUILIBRIUM MAPPING SOFTWARE

Documentation
 User Manuals
 - Windows
 - Linux
 - Installation
 Other Info
 - FAQs
 - Input File Example
 - Articles
 - Screenshots

Developers
 Core
 - Jeff Reeve
 - Bruce Rannala
 Contributors
 - Robert Lee
 - Ying Wang

Support
 - Report Bug
 - Request Help
 - GSF

2005-01-26
Features of DMLE+

The DMLE+ program allows multipoint LD mapping using an arbitrary number of SNPs or microsatellite markers. DMLE+ implements Markov chain Monte Carlo (MCMC) methods to allow Bayesian estimation of the posterior probability density of the position of a disease mutation relative to a set of markers.

Current Release (DMLE+ 2.2)

  • multipoint LD mapping using an arbitrary number of markers
  • integrates over uncertain genealogy of disease chromosomes
  • estimates Bayesian posterior probabilities of mutation location, disease allele age, and other parameters
  • uses either haplotype or genotype data (under simple models of disease inheritance)
  • allows for multiple marker alleles
  • integrates over uncertain allele frequencies in the normal (control) population
  • incorporates information from an annotated human genome sequence
  • Windows GUI and portable (UNIX) command line versions available
  • accomodates either linkage equilibrium or linkage disequilibrium in sample of controls*
  • allows slice sampling, uniform selection, or sliding window mechanisms for modifying mutation location in MCMC*
  • mutation age and branch length parameters adjusted separately in MCMC to improve mixing*
  • faster algorithms implemented for sampling topologies in MCMC*
  • linux version compiled with ICPC, rather than gcc, resulting in substantially faster execution*
*features new to release 2.2

Next Release (2.3)(late 2005)

  • uses either haplotype or genotype data (under complex models of disease inheritance)
  • allows for locus and allelic heterogeneity
  • allows for marker mutation under simple models (microsatellites)
  • takes account of the uncertain relationship between physical and linkage maps