Projects / CoaSim

CoaSim

CoaSim is a tool for simulating the coalescent process with recombination and gene conversion under the assumption of exponential population growth. It efficiently constructs the ancestral recombination graph for a given number of individuals and uses this to simulate samples of SNP and micro satellite haplotypes/genotypes. The generated sample can afterwards be separated in cases and controls, depending on the states of selected individual markers. The tool can accordingly also be used to construct cases and control data sets for association studies.

Tags Scientific/Engineering Bioinformatics Medical Science
Licenses GPL
Implementation C++ Scheme Python

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Rss Recent releases

Changes: This version adds explicit representation of migration events to the ARG. These can be used when exploring the ARG explicitly, or seen as annotations of local coalescent trees when these are printed.

Changes: This version adds explicit representation of migration events to the ARG. These can be used when exploring the ARG explicitly, or seen as annotations of local coalescent trees when these are printed.

  • Rrelease-mid
  •  27 Feb 2006 14:09
  • Rrelease-after

Changes: This release is the end of the beta test of the Python interface, and contains a few minor bugfixes and code cleanups.

  • Rrelease-mid
  •  23 Feb 2006 11:26
  • Rrelease-after

Changes: This version fixes a bug introduced in the last release that effectively disabled all bottlenecks and growth periods.

  • Rrelease-mid
  •  23 Feb 2006 11:26
  • Rrelease-after

Changes: This version fixes a bug introduced in the last release that effectively disabled all bottlenecks and growth periods.

Rss Recent comments

Rcomment-before 17 Oct 2005 00:36 Rcomment-trans mailund_birc Rcomment-after

CoaSim Application Note at BMC Bioinformatics

A paper describing CoaSim has just been publiced in BMC Bioinformatics:

CoaSim: A flexible environment for simulating genetic data under coalescent models (http://www.biomedcentral.com/1471-2105/6/252/abstract)

Thomas Mailund, Mikkel H. Schierup, Christian N.S. Pedersen, Peter J.M. Mechlenborg, Jesper N. Madsen, Leif Schauser

BMC Bioinformatics 2005, 6:252 (14 October 2005)

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