Factor Analysis Models

Navigation

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for ilia-kats from gravatar.com ilia-kats

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD 3-Clause License
  • Author: Ilia Kats
  • Maintainer: Ilia Kats
  • Requires: Python >=3.11
  • Provides-Extra: dev , doc , lazy , test
Classifiers
Report project as malware

Project description

MOFA-FLEX

PyPI Tests codecov Documentation

graphical abstract

MOFA-FLEX is a versatile factor analysis framework designed to streamline the construction and training of complex matrix factorisation models for omics data. It is built on a probabilistic programming-based Bayesian factor analysis framework that integrates concepts from multiple existing methods while remaining modular and extensible. MOFA-FLEX generalises widely used matrix factorisation tools by incorporating flexible prior options (including structured sparsity priors for multi-omics data and covariate-informed priors for spatio-temporal data), non-negativity constraints, and diverse data likelihoods - allowing users to mix and match components to suit their specific needs. Additionally, MOFA-FLEX introduces a novel module for integrating prior biological knowledge in the form of gene sets or, more generally, variable sets, enabling the inference of interpretable latent factors linked to specific molecular programs.

Getting started

Please refer to the documentation. In particular, the

Installation

You need to have Python 3.11 or newer installed on your system. If you don't have Python installed, we recommend installing Micromamba.

There are several alternative options to install MOFA-FLEX:

  1. Install the latest release of MOFA-FLEX from PyPI:
pip install mofaflex
  1. Install the latest development version:
pip install git+https://github.com/bioFAM/mofaflex.git@main

Release notes

See the changelog.

Contact

For questions and help requests, you can reach out in the discussions. If you found a bug, please use the issue tracker.

Citation

If you use MOFA-FLEX in your work, please cite

Qoku A, Rohbeck M, Walter FC, Kats I, Stegle O, and Buettner F. MOFA-FLEX: A Factor Model Framework for Integrating Omics Data with Prior Knowledge. Preprint at bioRxiv (2025). DOI: 10.1101/2025.11.03.686250.

BibTeX 
@article {mofaflex,
	author = {Qoku, Arber and Rohbeck, Martin and Walter, Florin Cornelius and Kats, Ilia and Stegle, Oliver and Buettner, Florian},
	title = {MOFA-FLEX: A Factor Model Framework for Integrating Omics Data with Prior Knowledge},
	eprint = {2025.11.03.686250},
	year = {2025},
	doi = {10.1101/2025.11.03.686250},
	URL = {https://www.biorxiv.org/content/early/2025/11/04/2025.11.03.686250},
	archiveprefix = {bioRxiv}
}

Project details

Verified details

These details have been verified by PyPI
Project links
GitHub Statistics
Maintainers
Avatar for ilia-kats from gravatar.com ilia-kats

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: BSD 3-Clause License
  • Author: Ilia Kats
  • Maintainer: Ilia Kats
  • Requires: Python >=3.11
  • Provides-Extra: dev , doc , lazy , test
Classifiers

Release history Release notifications | RSS feed

This version

0.1.0.post1

0.1.0

0.1.0rc2 pre-release

0.1.0rc1 pre-release

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mofaflex-0.1.0.post1.tar.gz (31.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mofaflex-0.1.0.post1-py3-none-any.whl (104.5 kB view details)

Uploaded Python 3

File details

Details for the file mofaflex-0.1.0.post1.tar.gz.

File metadata

  • Download URL: mofaflex-0.1.0.post1.tar.gz
  • Upload date:
  • Size: 31.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mofaflex-0.1.0.post1.tar.gz
Algorithm Hash digest
SHA256 2f6e92e48986f8f3414b72db946ce8a2ddda07a80bb7921fc6bd6660a94e91f9
MD5 d98db52d76b523e215fc3cb840e042a1
BLAKE2b-256 f60ecc915de590a37760aa26faaf7654521649b66cbe385269373d023dd52b3f

See more details on using hashes here.

Provenance

The following attestation bundles were made for mofaflex-0.1.0.post1.tar.gz:

Publisher: release.yaml on bioFAM/mofaflex

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mofaflex-0.1.0.post1-py3-none-any.whl.

File metadata

  • Download URL: mofaflex-0.1.0.post1-py3-none-any.whl
  • Upload date:
  • Size: 104.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mofaflex-0.1.0.post1-py3-none-any.whl
Algorithm Hash digest
SHA256 3bf9c2b91c657b3ff4eb6018b7dab14d4be1d18c4f134cc2a9470306c3836400
MD5 60b9c3a0c20c00a01646c5fc9a2782a1
BLAKE2b-256 63970998681157adbaba462eebb4ea113cbca08338253002ecbc70b4e10a5139

See more details on using hashes here.

Provenance

The following attestation bundles were made for mofaflex-0.1.0.post1-py3-none-any.whl:

Publisher: release.yaml on bioFAM/mofaflex

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page