A flexible and fast mixed model toolbox written in C++/python
Project description
# LIMIX
## What is LIMIX?
LIMIX is a flexible and efficient linear mixed model library with interfaces to Python.
Limix is currently mainly developed by
Franceso Paolo Casale (casale@ebi.ac.uk)
Danilo Horta (horta@ebi.ac.uk)
Christoph Lippert (chrisoph.a.lippert@gmail.com)
Oliver Stegle (stegle@ebi.ac.uk)
## Philosophy
Genomic analyses require flexible models that can be adapted to the needs of the user.
LIMIX is smart about how particular models are fit to safe computational cost.
## Installation:
* Recommended is an installation via pypi.
* pip install limix will work on most systems.
* LIMIX is particular easy to install using the anaconda python distribution: https://store.continuum.io/cshop/anaconda.
* If you want to install LIMIX from source you require:
Python:
- scipy, numpy, pandas, cython
* Swig:
- swig 2.0 or higher (only required if you need to recompile C++ interfaces)
## How to use LIMIX?
A good starting point is our package Vignettes. These tutorials can are available in 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.
Alternative the sources 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 by email: limix@mixed-models.org
## License
See [LICENSE] https://github.com/PMBio/limix/blob/master/license.txt
## What is LIMIX?
LIMIX is a flexible and efficient linear mixed model library with interfaces to Python.
Limix is currently mainly developed by
Franceso Paolo Casale (casale@ebi.ac.uk)
Danilo Horta (horta@ebi.ac.uk)
Christoph Lippert (chrisoph.a.lippert@gmail.com)
Oliver Stegle (stegle@ebi.ac.uk)
## Philosophy
Genomic analyses require flexible models that can be adapted to the needs of the user.
LIMIX is smart about how particular models are fit to safe computational cost.
## Installation:
* Recommended is an installation via pypi.
* pip install limix will work on most systems.
* LIMIX is particular easy to install using the anaconda python distribution: https://store.continuum.io/cshop/anaconda.
* If you want to install LIMIX from source you require:
Python:
- scipy, numpy, pandas, cython
* Swig:
- swig 2.0 or higher (only required if you need to recompile C++ interfaces)
## How to use LIMIX?
A good starting point is our package Vignettes. These tutorials can are available in 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.
Alternative the sources 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 by email: limix@mixed-models.org
## License
See [LICENSE] https://github.com/PMBio/limix/blob/master/license.txt
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
limix-0.7.73.tar.gz
(3.1 MB
view hashes)
Built Distribution
Close
Hashes for limix-0.7.73-cp27-cp27m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7b3a5d09df3b4c589df565151e3b534f86677c135ef6434532144b6c8f37ed4 |
|
MD5 | ea3e87d05a1c7e6fc1b574bbaf0e937b |
|
BLAKE2b-256 | 0c1c0f5072560c210fdb22dece1c94ffadc601e591d8dcd31b0ce2471a2e5da0 |