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dEploid is designed for deconvoluting mixed genomes with unknown proportions. Traditional ‘phasing’ programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting.
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README.md

License (GPL version 3) Build Status CircleCI Coverage Status Documentation Status Docker Status

dEploid is designed for deconvoluting mixed genomes with unknown proportions. Traditional ‘phasing’ programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting.

Please see the documentation for further details.

Installation

You can also install dEploid directly from the git repository. Here, you will need autoconf, check whether this is already installed by running:

$ which autoconf

On Debian/Ubuntu based systems:

$ apt-get install build-essential autoconf autoconf-archive libcppunit-dev zlib1g-dev

On Mac OS:

$ port install automake autoconf autoconf-archive cppunit

Afterwards you can clone the code from the github repository,

$ git clone git@github.com:mcveanlab/DEploid.git
$ cd DEploid

and build the binary using

$ ./bootstrap
$ make

Usage

Please see the documentation for further details.

Licence

You can freely use all code in this project under the conditions of the GNU GPL Version 3 or later.

Citation

If you use dEploid with the flag -ibd, please cite the following paper:

Zhu, J. S., J. A. Hendry, J. Almagro-Garcia, R. D. Pearson, R. Amato, A. Miles, D. J. Weiss, T. C. D. Lucas, M. Nguyen, P. W. Gething, D. Kwiatkowski, G. McVean, and for the Pf3k Project. (2018) The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria. biorxiv, doi: https://doi.org/10.1101/387266.

If you use dEploid in your work, please cite the program:

Zhu, J. S. J. A. Garcia G. McVean. (2018) Deconvolution of multiple infections in Plasmodium falciparum from high throughput sequencing data. Bioinformatics 34(1), 9-15. doi: https://doi.org/10.1093/bioinformatics/btx530.

This code is associated with the paper from Zhu et al., "The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria". eLife, 2019. http://dx.doi.org/10.7554/eLife.40845

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