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A flexible and fast mixed model toolbox.

Project description

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Limix is a flexible and efficient linear mixed model library with interfaces to Python. Genomic analyses require flexible models that can be adapted to the needs of the user. Limix is smart about how particular models are fitted to save computational cost.

LATEST: iSet, interaction set tests for gene-context interactions, is now in Limix.

Installation

Using Conda package manager

Conda is a package manager designed for Python and R users/developers of scientific tools, and comes with the Anaconda distribution. Currently we support this installation for Linux 64 bits and OSX operating systems.

conda install -c conda-forge limix

Using Pip

If you don’t have Conda (or don’t want to use the above method), Limix can be installed via Pip package manager.

pip install limix

This approach is not as straightforward as the first one because it requires compilation of C/C++ and (potentially) Fortran code, and some understanding of dependency resolution is likely to be required. We provide bellow recipes for some popular Limix distributions, assuming you have the wget command line tool.

  • Ubuntu

    bash <(wget -O - https://raw.githubusercontent.com/PMBio/limix/master/deploy/apt_limix_install)
  • Fedora

    bash <(wget -O - https://raw.githubusercontent.com/PMBio/limix/master/deploy/dnf_limix_install)
  • OpenSUSE

    bash <(wget -O - https://raw.githubusercontent.com/PMBio/limix/master/deploy/zypper_limix_install)

From source

This is more tricky in terms of dependency resolution but useful for developers.

git clone https://github.com/PMBio/limix.git
cd limix
python setup.py install # or python setup.py develop

Usage

A good starting point is our package Vignettes. These tutorials are available from this repository: https://github.com/PMBio/limix-tutorials.

The main package vignette can also be viewed using the ipython notebook viewer: http://nbviewer.ipython.org/github/pmbio/limix-tutorials/blob/master/index.ipynb.

Alternatively, the source file is available in the separate Limix tutorial repository: https://github.com/PMBio/limix-tutorials

Problems

If you want to use Limix and encounter any issues, please contact us via limix@mixed-models.org.

Authors

  • Franceso Paolo Casale (casale@ebi.ac.uk)

  • Danilo Horta (horta@ebi.ac.uk)

  • Christoph Lippert (christoph.a.lippert@gmail.com)

  • Oliver Stegle (stegle@ebi.ac.uk)

License

See Apache License (Version 2.0, January 2004).

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