gneiss 0.4.6

Compositional data analysis tools and visualizations

gneiss

Canonically pronouced nice

gneiss is a compositional data analysis and visualization toolbox designed for analyzing high dimensional proportions. See here for API documentation.

Note that gneiss is not compatible with python 2, and is compatible with Python 3.4 or later. gneiss is currently in alpha. We are actively developing it, and backward-incompatible interface changes may arise.

Installation

To install this package, it is recommended to use conda. First make sure that the appropriate channels are configured.

conda config --add channels https://conda.anaconda.org/bioconda
conda config --add channels https://conda.anaconda.org/biocore
conda config --add channels https://conda.anaconda.org/qiime2
conda config --add channels https://conda.anaconda.org/qiime2/label/r2017.6

Then gneiss can be installed in a conda environment as follows

conda create -n gneiss_env gneiss

To install the most up to date version of gneiss, run the following command

pip install git+https://github.com/biocore/gneiss.git

Tutorials

• What are balances

Qiime2 tutorials

• Linear regression on balances in the 88 soils
• Linear mixed effects models on balances in a CF study
• Linear regression on balances in the Chronic Fatigue Syndrome

Python tutorials

• Linear regression on balances in the 88 soils
• Linear mixed effects models on balances in a CF study
• Linear regression on balances in the Chronic Fatigue Syndrome

If you use this software package in your own publications, please cite it at

Morton JT, Sanders J, Quinn RA, McDonald D, Gonzalez A, Vázquez-Baeza Y, 
Navas-Molina JA, Song SJ, Metcalf JL, Hyde ER, Lladser M, Dorrestein PC, 
Knight R. 2017. Balance trees reveal microbial niche differentiation. 
mSystems 2:e00162-16. https://doi.org/10.1128/mSystems.00162-16.