mowgli 0.1.0

Mowgli: Multi Omics Wasserstein inteGrative anaLysIs.

Mowgli: Multi Omics Wasserstein inteGrative anaLysIs

Mowgli is a novel method for the integration of paired multi-omics data with any type and number of omics, combining integrative Nonnegative Matrix Factorization and Optimal Transport. Read the preprint!

Install the package

Mowgli is implemented as a Python package seamlessly integrated within the scverse ecosystem, in particular Muon and Scanpy.

via PyPI (recommended)

pip install mowgli

via GitHub (development version)

git clone [e-mail]:cantinilab/Mowgli.git
pip install ./Mowgli/

Getting started

Mowgli takes as an input a Muon object and populates its obsm and uns fiels with the embeddings and dictionaries, respectively. Visit mowgli.rtfd.io for more documentation and tutorials.

from mowgli import models
import muon as mu
import scanpy as sc

# Load data into a Muon object.
mdata = mu.load_h5mu("my_data.h5mu")

# Initialize and train the model.
model = models.MowgliModel(latent_dim=15)
model.train(mdata)

# Visualize the embedding with UMAP.
sc.pp.neighbors(mdata, use_rep="W_OT")
sc.tl.umap(mdata)
sc.pl.umap(mdata)

Our preprint

Preprint available soon!

If you're looking for the repository with code to reproduce the experiments in our preprint, here is is!