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        "description": "FaST-LMM\r\n=================================\r\n\r\nFaST-LMM, which stands for Factored Spectrally Transformed Linear Mixed Models, is a program for performing both single-SNP and SNP-set genome-wide association studies (GWAS) on extremely large data sets.  This release contains the improvements described in Widmer _et al._, _Scientific Reports_ 2014, and tests for epistasis.\r\n\r\nOur documentation (including live examples) is also available as ipython notebooks:\r\n\r\n* Main Functions: https://github.com/MicrosoftGenomics/FaST-LMM/blob/master/doc/ipynb/FaST-LMM.ipynb\r\n* Heritability with Spatial Correction (described in Heckerman _et al._, _PNAS_ 2016): https://github.com/MicrosoftGenomics/FaST-LMM/blob/master/doc/ipynb/heritability_si.ipynb\r\n\r\nAdditionally, API documentation is available:\r\nhttp://microsoftgenomics.github.io/FaST-LMM/\r\n\r\nA C++ version, which is generally less functional, is available at http://research.microsoft.com/en-us/downloads/30260656-0f99-4ae0-b7ce-08157b50d4d9/\r\n\r\nQuick install:\r\n=================================\r\n\r\nIf you have pip installed, installation is as easy as:\r\n\r\n    pip install fastlmm\r\n\r\nDetailed Package Install Instructions:\r\n==================================================================\r\n\r\nfastlmm has the following dependencies:\r\n\r\npython 2.7\r\n\r\nPackages:\r\n\r\n* numpy\r\n* scipy\r\n* matplotlib\r\n* pandas\r\n* scikit.learn (sklearn)\r\n* cython\r\n* pysnptools\r\n* optional: [statsmodels -- install only required for logistic-based tests, not the standard linear LRT]\r\n\r\n\r\n(1) Installation of dependent packages\r\n-------------------------------------------\r\n\r\nWe highly recommend using a python distribution such as \r\nAnaconda (https://store.continuum.io/cshop/anaconda/) \r\nor Enthought (https://www.enthought.com/products/epd/free/).\r\nBoth these distributions can be used on linux and Windows, are free \r\nfor non-commercial use, and optionally include an MKL-compiled distribution\r\nfor optimal speed. This is the easiest way to get all the required package\r\ndependencies.\r\n\r\n\r\n(2) Installing from source\r\n-------------------------------------------\r\n\r\nGo to the directory where you copied the source code for fastlmm.\r\n\r\nOn linux:\r\n\r\nAt the shell, type: \r\n\r\n    sudo python setup.py install\r\n\r\n\r\nOn Windows:\r\n\r\nAt the OS command prompt, type \r\n\r\n    python setup.py install\r\n\r\n\r\n\r\nFor developers (and also to run regression tests)\r\n=====================================================\r\n\r\nWhen working on the developer version, first add the src directory of the package to your PYTHONPATH \r\nenvironment variable.\r\n\r\nFor building C-extensions, first make sure all of the above dependencies are installed (including cython)\r\n\r\nTo build extension (from .\\src dir), type the following at the OS prompt:\r\n\r\n    python setup.py build_ext --inplace\r\n\r\n\r\nNote, if this fails with a gcc permission denied error, then specifying the correct compiler will\r\nlikely fix the problem, e.g.\r\n\r\n    python setup.py build_ext --inplace --compiler=msvc\r\n\r\n\r\nDon't forget to set your PYTHONPATH to point to the directory above the one named fastlmm in\r\nthe fastlmm source code. For e.g. if fastlmm is in the [somedir] directory, then\r\nin the unix shell use:\r\n\r\n    export PYTHONPATH=$PYTHONPATH:[somedir]\r\n\r\nOr in the Windows DOS terminal,\r\none can use: \r\n\r\n    set PYTHONPATH=%PYTHONPATH%;[somedir]\r\n\r\n(or use the Windows GUI for env variables).\r\n\r\nNote for Windows: You must have Visual Studio installed. If you have VisualStudio2008 installed \r\n(which was used to build python2.7) you need to nothing more. Otherwise, follow these instructions:\r\n\r\nIf you have Visual Studio 2010 installed, execute:\r\n\r\n    SET VS90COMNTOOLS=%VS100COMNTOOLS%\r\n\r\nor with Visual Studio 2012 installed:\r\n\r\n    SET VS90COMNTOOLS=%VS110COMNTOOLS%\r\n\r\nor with Visual Studio 2013 installed:\r\n\r\n    SET VS90COMNTOOLS=%VS120COMNTOOLS%\r\n\r\nor with Visual Studio 2015 installed:\r\n\r\n    SET VS90COMNTOOLS=%VS130COMNTOOLS%\r\n\r\nor with Visual Studio 2017 installed:\r\n\r\n    SET VS90COMNTOOLS=%VS140COMNTOOLS%\r\n\r\n\r\nRunning regression tests\r\n--------------------------------------\r\n\r\nFrom the directory tests at the top level, run:\r\n\r\n    python test.py\r\n\r\nThis will run a\r\nseries of regression tests, reporting \".\" for each one that passes, \"F\" for each\r\none that does not match up, and \"E\" for any which produce a run-time error. 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