Metadata-Version: 2.1
Name: mosaicmpi
Version: 2.3.2
Summary: mosaicMPI: Mosaic Multi-resolution Program Integration
Home-page: https://github.com/MorrissyLab/mosaicMPI
Author: Ted Verhey
Author-email: tbverhey@ucalgary.ca
Project-URL: Bug Tracker, https://github.com/MorrissyLab/mosaicMPI/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: anndata>=0.8.0
Requires-Dist: seaborn
Requires-Dist: statsmodels
Requires-Dist: networkx
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scipy>=1.9.0
Requires-Dist: matplotlib
Requires-Dist: upsetplot
Requires-Dist: tomli
Requires-Dist: tomli-w
Requires-Dist: distinctipy
Requires-Dist: click
Requires-Dist: pygraphviz
Requires-Dist: igraph
Requires-Dist: pyyaml
Requires-Dist: scikit-learn
Requires-Dist: fastcluster
Requires-Dist: scanpy
Requires-Dist: tqdm

![mosaicMPI logo](https://github.com/MorrissyLab/mosaicMPI/blob/main/docs/source/_static/img/logo.png?raw=True)

# mosaicMPI: mosaic multi-resolution program integration

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[![DOI:10.1101/2023.08.18.553919](http://img.shields.io/badge/DOI-10.1101/2023.08.18.553919-B31B1B.svg)](https://doi.org/10.1101/2023.08.18.553919)

Authors: [Ted Verhey](https://github.com/verheytb), [Sorana Morrissy](https://github.com/ancasorana)

Contributors: Hyojin Song, Aaron Gillmor, Courtney Hall

**mosaicMPI** is a Python package enabling mosaic integration of bulk, single-cell, and spatial expression data through program-level integration.
Programs are first discovered using consensus non-negative matrix factorization and then integrated using a flexible network-based approach to
group similar programs together across resolutions and datasets. Program communities are then interpreted using sample/cell metadata and gene set analyses. Integrative program communities enable metadata transfer across datasets.

## ⚡Main Features

Here are just a few of the things that mosaicMPI does well:

- Identifies interpretable, non-negative programs at multiple resolutions
- Mosaic integration does not require subsetting features/genes to
  a shared or overdispersed subset
- Multi-omics integration without shared sample IDs
- Ideal for incremental integration (adding datasets one at a time) since
  deconvolution is performed independently on each dataset
- Integration performs well even when the datasets have mismatched features
  (eg. Microarray, RNA-Seq, Proteomics) or sparsity (eg single-cell vs bulk RNA-Seq and ATAC-Seq)
- Metadata transfer across datasets
- Command-line interface for rapid data exploration and python
  interface for extensibility and flexibility

## 🔧 Install

### 🧰 System Requirements

- Compatible with and tested on OS X, Windows and Linux systems
- Memory usage depends on size and number of datasets

### ✨ Latest Release
Install the package with `conda`:
```bash
# create an environment called mosaic and install
conda create -n mosaic -c conda-forge mosaicmpi
conda activate mosaic
```

For ssGSEA analysis, you will also need to install GSEApy into the same environment.

```bash
# if you have conda (MacOS_x86-64 and Linux only)
conda install -c bioconda gseapy
# Windows and MacOS_ARM64 (M1/2-Chip)
pip install gseapy
```

## 📖 Documentation

Read the [documentation](https://mosaicmpi.readthedocs.io/).

## 💭 Getting Help

For errors arising during use of mosaicMPI, create and browse issues in the [GitHub "issues" tab](https://github.com/MorrissyLab/mosaicMPI/issues).
