Metadata-Version: 1.2
Name: deicode
Version: 0.2.2
Summary: Robust Aitchison compositional biplots from sparse count data
Home-page: UNKNOWN
Author: deicode development team
Author-email: cameronmartino@gmail.com
Maintainer: deicode development team
Maintainer-email: cameronmartino@gmail.com
License: BSD-3-Clause
Description: [![Build Status](https://travis-ci.org/biocore/DEICODE.svg?branch=master)](https://travis-ci.org/biocore/DEICODE)
        [![Coverage Status](https://coveralls.io/repos/github/biocore/DEICODE/badge.svg?branch=master)](https://coveralls.io/github/biocore/DEICODE?branch=master)
        
        DEICODE is a tool box for running Robust Aitchison PCA on sparse compositional omics datasets, linking specific features to beta-diversity ordination. 
        
        ## Installation
        
        To install the most up to date version of deicode, run the following command
        
            # pip (only supported for QIIME2 >= 2018.8)
            pip install deicode
        
            # conda (only supported for QIIME2 >= 2019.1)
            conda install -c conda-forge deicode 
        
        **Note**: that deicode is not compatible with python 2, and is compatible with Python 3.4 or later. deicode is currently in alpha. We are actively developing it, and backward-incompatible interface changes may arise.
        
        ## Using DEICODE as a standalone tool
        
        ```
        $ deicode --help
        Usage: deicode [OPTIONS]
        
          Runs RPCA with an rclr preprocessing step.
        
        Options:
          --in-biom TEXT               Input table in biom format.  [required]
          --output-dir TEXT            Location of output files.  [required]
          --rank INTEGER               The underlying low-rank structure (suggested: 1
                                       < rank < 10) [minimum 2]  [default: 3]
          --min-sample-count INTEGER   Minimum sum cutoff of sample across all
                                       features  [default: 500]
          --min-feature-count INTEGER  Minimum sum cutoff of features across all
                                       samples  [default: 10]
          --iterations INTEGER         The number of iterations to optimize the
                                       solution (suggested to be below 100; beware of
                                       overfitting) [minimum 1]  [default: 5]
          --help                       Show this message and exit.
        ```
        
        ## Using DEICODE inside [QIIME 2](https://qiime2.org/)
        
        * The QIIME2 forum tutorial can be found [here](https://forum.qiime2.org/t/robust-aitchison-pca-beta-diversity-with-deicode/8333).
        * The official plugin docs and tutorial can be found [here](https://library.qiime2.org/plugins/deicode).
        * The in-repo tutorial can be found [here](https://github.com/biocore/DEICODE/blob/master/ipynb/tutorials/moving-pictures.md).
        
        ## Other Resources
        
        * [Aitchison Distance Introduction](https://github.com/biocore/DEICODE/blob/master/ipynb/introduction.ipynb)
        
        - The code for OptSpace was translated to python from a [MATLAB package](http://swoh.web.engr.illinois.edu/software/optspace/code.html) maintained by Sewoong Oh (UIUC).
        - Transforms and PCoA : [Scikit-bio](http://scikit-bio.org)
        - Data For Examples : [Qiita](https://qiita.ucsd.edu/)
        
        #### Simulation and Benchmarking
        
        * [simulations and case studies](https://github.com/cameronmartino/deicode-benchmarking)
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
