Multi-Omics Factor Analysis

muon is a multimodal omics Python framework

MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

Multi-task deep learning framework for multi-omics data analysis

Multimodal Data (.h5mu) implementation for Python

Deep learning model for single-cell inference of multi-omic profiles from a single input modality.

A bioinformatics API to interface with public multi-omics bio databases for wicked fast data integration.

Analyses for "State of the field in multi-omics research: from computational needs to data mining and sharing"

.h5mu files interface for Seurat

R package for High dimensional data analysis and integration with O2PLS!

Model-based Genomically Informed High-dimensional Predictor of Microbial Community Metabolic Profiles

Tutorials for multimodal omics data analysis

Integrated Machine Learning for Multi-omics Classification and Prediction

Time-Course Multi-Omics data integration

MONTI is a tool for analyzing large multi-omics cancer cohort data in association with clinical featuers

Disease subnetwork detection with explainable Graph Neural Networks

Muon for Julia

CITEViz: Replicating the Interactive Flow Cytometry Workflow in CITE-Seq

Pipeline for HiCAR data, a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility and cis-regulatory chromatin contacts.