cnmfsns 1.2.1

cNMF Solution Network Space

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cNMF-SNS: powerful factorization-based multi-omics integration toolkit

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3509134.svg)](https://doi.org/10.5281/zenodo.3509134)

cNMF-SNS (consensus Non-negative Matrix Factorization Solution Network Space) is a Python package enabling integration of bulk, single-cell, and spatial expression data between and within datasets. cNMF provides a robust, unsupervised deconvolution of each dataset into gene expression programs (GEPs). Network-based integration of GEPs enables flexible integration of many datasets across assays (eg. Protein, RNA-Seq) and patient cohorts.

Communities with GEPs from multiple datasets can be annotated with dataset-specific annotations to facilitate interpretation.

⚡Main Features

Here are just a few of the things that cNMF-SNS does well:

• Integration of expression data does not require subsetting features/genes to a shared or 'overdispersed' subset
• Ideal for incremental integration (adding datasets one at a time) since deconvolution is performed independently on each dataset generating invariant GEPs
• Does not assume the same level of sparsity/depth (single-cell, bulk)
• Identifies interpretable, additive non-negative gene expression programs
• Two interfaces: command-line interface for rapid data exploration and python interface for extensibility and flexibility

🔧 Install

☁️ Public Release

Install the package with conda:

conda install -c conda-forge cnmfsns

✨ Latest version from GitHub

Before installing cNMF-SNS using pip, it is recommended to first set up a separate conda environment and have conda manage as many dependencies as possible.

conda create --name cnmfsns -c conda-forge python=3.10 anndata pandas numpy scipy matplotlib upsetplot httplib2 tomli tomli-w click pygraphviz python-igraph semantic_version yaml scikit-learn fastcluster scanpy pyyaml gseapy=1.0.3
conda activate cnmfsns
pip install git+https://github.com/MorrissyLab/cNMF-SNS.git

📖 Documentation

📓 Python interface tutorial

To get started, sample proteomics datasets and a Jupyter notebook tutorial is available here.

⌨️ Command line interface

See the command line interface documentation.

💭 Getting Help

For errors arising during use of cNMF-SNS, create and browse issues in the GitHub "issues" tab.