q2-gglasso

bio-datascience

BSD License Python version Documentation Status CI Code style: black

A QIIME 2 plugin for solving General Graphical Lasso (GGLasso) problems with microbiome data including:

  • Single Graphical Lasso (SGL)
  • Adaptive SGL
  • SGL with latent variables
  • Multiple Graphical Lasso (MGL)
  • MGL with latent variables
  • GGL in the nonconforming case

📚 Documentation | 📂 Tutorial & Examples

Installation¶

First, make sure you have GGLasso is installed:

conda install -q gglasso

OR

pip install gglasso

Next to install the plugin:

pip install git+https://github.com/bio-datascience/q2-gglasso.git
qiime dev refresh-cache

Usage Tutorial¶

A complete tutorial on using q2-gglasso for microbiome data analysis — including preprocessing, CLR transformation, model fitting, and visualization — is available at:

👉 Atacama Soil Microbiome Tutorial

This tutorial includes:

  • Input formatting and CLR transformation
  • Applications of SGL, adaptive SGL, and SGL with latent variables
  • Network visualizations of ASV associations
  • Covariate analysis and interpretation

Citation¶

If you use q2-gglasso, please cite:

Schaipp, F., Vlasovets, O., & Müller, C. L. (2021). GGLasso – a Python package for General Graphical Lasso computation. Journal of Open Source Software, 6(68), 3865. https://doi.org/10.21105/joss.03865

License¶

BSD 3-Clause License. See LICENSE for details.

BSD License Python version Documentation Status CI Code style: black

A QIIME 2 plugin for solving General Graphical Lasso (GGLasso) problems with microbiome data including:

  • Single Graphical Lasso (SGL)
  • Adaptive SGL
  • SGL with latent variables
  • Multiple Graphical Lasso (MGL)
  • MGL with latent variables
  • GGL in the nonconforming case

📚 Documentation | 📂 Tutorial & Examples

Installation¶

First, make sure you have GGLasso is installed:

conda install -q gglasso

OR

pip install gglasso

Next to install the plugin:

pip install git+https://github.com/bio-datascience/q2-gglasso.git
qiime dev refresh-cache

Usage Tutorial¶

A complete tutorial on using q2-gglasso for microbiome data analysis — including preprocessing, CLR transformation, model fitting, and visualization — is available at:

👉 Atacama Soil Microbiome Tutorial

This tutorial includes:

  • Input formatting and CLR transformation
  • Applications of SGL, adaptive SGL, and SGL with latent variables
  • Network visualizations of ASV associations
  • Covariate analysis and interpretation

Citation¶

If you use q2-gglasso, please cite:

Schaipp, F., Vlasovets, O., & Müller, C. L. (2021). GGLasso – a Python package for General Graphical Lasso computation. Journal of Open Source Software, 6(68), 3865. https://doi.org/10.21105/joss.03865

License¶

BSD 3-Clause License. See LICENSE for details.

BSD License Python version Documentation Status CI Code style: black

A QIIME 2 plugin for solving General Graphical Lasso (GGLasso) problems with microbiome data including:

  • Single Graphical Lasso (SGL)
  • Adaptive SGL
  • SGL with latent variables
  • Multiple Graphical Lasso (MGL)
  • MGL with latent variables
  • GGL in the nonconforming case

📚 Documentation | 📂 Tutorial & Examples

Installation¶

First, make sure you have GGLasso is installed:

conda install -q gglasso

OR

pip install gglasso

Next to install the plugin:

pip install git+https://github.com/bio-datascience/q2-gglasso.git
qiime dev refresh-cache

Usage Tutorial¶

A complete tutorial on using q2-gglasso for microbiome data analysis — including preprocessing, CLR transformation, model fitting, and visualization — is available at:

👉 Atacama Soil Microbiome Tutorial

This tutorial includes:

  • Input formatting and CLR transformation
  • Applications of SGL, adaptive SGL, and SGL with latent variables
  • Network visualizations of ASV associations
  • Covariate analysis and interpretation

Citation¶

If you use q2-gglasso, please cite:

Schaipp, F., Vlasovets, O., & Müller, C. L. (2021). GGLasso – a Python package for General Graphical Lasso computation. Journal of Open Source Software, 6(68), 3865. https://doi.org/10.21105/joss.03865

License¶

BSD 3-Clause License. See LICENSE for details.

BSD License Python version Documentation Status CI Code style: black

A QIIME 2 plugin for solving General Graphical Lasso (GGLasso) problems with microbiome data including:

  • Single Graphical Lasso (SGL)
  • Adaptive SGL
  • SGL with latent variables
  • Multiple Graphical Lasso (MGL)
  • MGL with latent variables
  • GGL in the nonconforming case

📚 Documentation | 📂 Tutorial & Examples

Installation¶

First, make sure you have GGLasso is installed:

conda install -q gglasso

OR

pip install gglasso

Next to install the plugin:

pip install git+https://github.com/bio-datascience/q2-gglasso.git
qiime dev refresh-cache

Usage Tutorial¶

A complete tutorial on using q2-gglasso for microbiome data analysis — including preprocessing, CLR transformation, model fitting, and visualization — is available at:

👉 Atacama Soil Microbiome Tutorial

This tutorial includes:

  • Input formatting and CLR transformation
  • Applications of SGL, adaptive SGL, and SGL with latent variables
  • Network visualizations of ASV associations
  • Covariate analysis and interpretation

Citation¶

If you use q2-gglasso, please cite:

Schaipp, F., Vlasovets, O., & Müller, C. L. (2021). GGLasso – a Python package for General Graphical Lasso computation. Journal of Open Source Software, 6(68), 3865. https://doi.org/10.21105/joss.03865

License¶

BSD 3-Clause License. See LICENSE for details.