Metadata-Version: 1.0
Name: struct-lmm
Version: 0.0.9
Summary: Linear mixed model to study multivariate genotype-environment interactions
Home-page: https://github.com/limix/struct-lmm
Author: StructLMM developers
Author-email: casale@ebi.ac.uk
License: Apache License 2.0'
Description-Content-Type: UNKNOWN
Description: struct-lmm
        ==========
        
        Structured Linear Mixed Model (StructLMM) is a computationally efficient
        method to test for and characterize loci that interact with multiple
        environments.
        
        Getting Started
        ---------------
        
        StructLMM is Python package implemented in both Python and R programming
        languages that depends on some libraries implemented in C. To make its
        installation as easy as possible, we make use
        `conda <https://conda.io/>`__, a package manager for software
        implemented in Python, R, and C/C++ (among others) languages.
        
        Interaction with StructLMM happens in the terminal via the following
        command line tools installed with the package, and described at the
        `Command Line
        Interface <http://struct-lmm.readthedocs.io/en/latest/commandline.html>`__
        section of the `documentation <http://struct-lmm.readthedocs.io/>`__:
        
        -  norm\_env
        -  struct\_lmm\_analyze
        -  lmm\_int\_analyze
        -  lmm\_analyze
        -  struct\_lmm\_analyze
        
        Requisites
        ~~~~~~~~~~
        
        The installation script runs in on GNU/Linux and macOS operating
        systems. It requires either
        `wget <https://www.gnu.org/software/wget/>`__ or
        `curl <https://curl.haxx.se/>`__ command line tools in case
        `conda <https://conda.io/>`__ is not already installed. In any case, the
        installation script will inform the user if it cannot proceed.
        Otherwise, the StructLMM dependencies is automatically installed and
        does not require user intervention.
        
        Install
        ~~~~~~~
        
        For Linux and macOS operating systems, struct-lmm can be install from
        the command line by entering
        
        .. code:: bash
        
            bash <(curl -fsSL https://raw.githubusercontent.com/limix/struct-lmm/master/install)
        
        The user might be prompted to install conda in case he/she does not have
        it, and will warn the user if for some reason the installation process
        cannot proceed. The whole installation process should take less than 15
        minutes and mainly consists in downloading essential R and Python
        packages for a working environment.
        
        Usage example
        -------------
        
        StructLMM can be run from the command line using the following
        
        .. code:: bash
        
            wget http://www.ebi.ac.uk/~casale/data_structlmm.zip
            unzip data_structlmm.zip
        
            BFILE=data_structlmm/chrom22_subsample20_maf0.10
            PFILE=data_structlmm/expr.csv
            EFILE0=data_structlmm/env.txt
            EFILE=data_structlmm/env_norm.txt
        
            struct_lmm_analyze --bfile $BFILE --pfile $PFILE --pheno_id gene10 --efile $EFILE --ofile out/results.res --idx_start 0 --idx_end 1000 --batch_size 100 --unique_variants
        
        Further examples can be found at http://struct-lmm.readthedocs.io/.
        
        Documentation
        -------------
        
        Documentation is available online at http://struct-lmm.readthedocs.io/.
        
        Problems
        --------
        
        If you encounter any problem, please, consider submitting a `new
        issue <https://github.com/limix/struct-lmm/issues/new>`__.
        
        Authors
        -------
        
        -  **Rachel Moore** - https://github.com/rm18
        -  **Danilo Horta** - https://github.com/horta
        -  **Francesco Paolo Casale** - https://github.com/fpcasale
        
        License
        -------
        
        This project is licensed under the Apache License (Version 2.0, January
        2004) - see the `LICENSE <LICENSE>`__ file for details
        
Platform: UNKNOWN
