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.

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Recent releases

  •  28 Feb 2006 21:59

    Release Notes: 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.

    •  28 Feb 2006 10:28

      Release Notes: 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.

      •  27 Feb 2006 22:09

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

        •  23 Feb 2006 19:26

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

          •  23 Feb 2006 19:26

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

            Recent comments

            17 Oct 2005 00:36 mailund_birc

            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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