Robust Aitchison compositional biplots from sparse count data
Project description
[![Build Status](https://travis-ci.org/biocore/DEICODE.svg?branch=master)](https://travis-ci.org/biocore/DEICODE)
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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)
[![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)
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