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'''minimac''' is a low memory, computationally efficient implementation of the MaCH algorithm for genotype imputation. It is designed to work on phased genotypes and can handle very large reference panels with hundreds or thousands of haplotypes. The name has two parts. The first, "mini", refers to the modest amount of computational resources it requires. The second, "mac", is short hand for [[MaCH]], our widely used algorithm for genotype imputation.
'''minimac''' is a low memory, computationally efficient implementation of the MaCH algorithm for genotype imputation. It is designed to work on phased genotypes and can handle very large reference panels with hundreds or thousands of haplotypes. The name has two parts. The first, "mini", refers to the modest amount of computational resources it requires. The second, "mac", is short hand for [[MaCH]], our widely used algorithm for genotype imputation.
= Download =
A full release of <code>minimac</code> is expected here in October 2010. In the meantime, a binary only Linux version of minimac is available [http://www.sph.umich.edu/csg/abecasis/downloads/minimac-beta-2010.10.12.tar.gz from here] for those who are eager to try it out. If you use this beta version, please be sure to stop by the [http://www.sph.umich.edu/csg/abecasis/MaCH/downloads/ MaCH download page] and fill out the registration form, so that we can let you know when an official release is available.
== Multiprocessor Version ==
The current version of minimac comes in two flavours, <code>minimac</code> and <code>minimac-omp</code>. The latter version uses the [[OpenMP]] protocol to support multi-threading, resulting in faster throughput.
== Questions and Comments ==
Please contact [mailto:goncalo@umich.edu Goncalo Abecasis] or [mailto:cfuchsb@umich.edu Christian Fuchsberger].
= Performance =
= Performance =
In this updated formula, N<sub>rounds</sub> represents the number of iterations used for parameter refinement and N<sub>states</sub> represents the maximum number of reference and target haplotypes considered for each update.
In this updated formula, N<sub>rounds</sub> represents the number of iterations used for parameter refinement and N<sub>states</sub> represents the maximum number of reference and target haplotypes considered for each update.
= Getting Started =
= Getting Started =
