https://github.com/saezlab/liana-py

LIANA+: an all-in-one framework for cell-cell communication
https://github.com/saezlab/liana-py

cell-cell-communication ligand-receptor python single-cell single-cell-rna-seq spatial spatialomics

Last synced: 6 months ago
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LIANA+: an all-in-one framework for cell-cell communication

• Host: GitHub
• URL: https://github.com/saezlab/liana-py
• Owner: saezlab
• License: gpl-3.0
• Created: 2022-09-22T13:20:35.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2024-07-18T11:49:07.000Z (about 1 year ago)
• Last Synced: 2024-08-07T13:28:08.758Z (about 1 year ago)
• Topics: cell-cell-communication, ligand-receptor, python, single-cell, single-cell-rna-seq, spatial, spatialomics
• Language: Python
• Homepage: http://liana-py.readthedocs.io/
• Size: 224 MB
• Stars: 141
• Watchers: 2
• Forks: 16
• Open Issues: 27
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# LIANA+: an all-in-one cell-cell communication framework 

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LIANA+ is a scalable framework that adapts and extends existing methods and knowledge to study cell-cell communication in single-cell, spatially-resolved, and multi-modal omics data. It is part of the [scverse ecosystem](https://github.com/scverse), and relies on [AnnData](https://github.com/scverse/anndata) & [MuData](https://github.com/scverse/mudata) objects as input.



## Contributions

We welcome suggestions, ideas, and contributions! Please do not hesitate to contact us, open issues, and check the [contributions guide](https://liana-py.readthedocs.io/en/latest/contributing.html).

## Vignettes

A set of extensive vignettes can be found in the [LIANA+ documentation](https://liana-py.readthedocs.io/en/latest/).

## Decision Tree

### Does the data contain spatial coordinates?

#### Yes

- **Q: Bivariate or unsupervised, multi-variate, and multi-view analysis?**

  - **Bivariate:**

    - **Q: Are you interested in identifying the subregions of interactions (i.e., local interactions)?**

      - **Yes:** Check the [**Local** Bivariate Metrics](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html#Bivariate-Ligand-Receptor-Relationships)

      - **No:** Check the [**Global** Bivariate Metrics](https://liana-py.readthedocs.io/en/latest/notebooks/bivariate.html#Bivariate-Ligand-Receptor-Relationships)

  - **Unsupervised:** [Multi-view learning](https://liana-py.readthedocs.io/en/latest/notebooks/misty.html)

#### No

- **Q: Are you interested in comparing CCC across samples?**

  - **Yes:**

    - **Q: Are you interested in a specific contrast?**

      - **Yes:** [Differential Contrasts and Downstream Signalling](https://liana-py.readthedocs.io/en/latest/notebooks/targeted.html)

      - **No:** Unsupervised Cross-conditional LR inference with [MOFA+](https://liana-py.readthedocs.io/en/latest/notebooks/mofatalk.html) or [Tensor-cell2cell](https://liana-py.readthedocs.io/en/latest/notebooks/liana_c2c.html)

  - **No:** [Steady-state Ligand-Receptor inference](https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html)

### Is your data Multi-modal?

- **Spatial:** [Integrating Multi-Modal Spatially-Resolved Technologies](https://liana-py.readthedocs.io/en/latest/notebooks/sma.html)

- **Non-Spatial:** [Integrating Multi-Modal Single-Cell Technologies](https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html)

#### Infer Metabolite-mediated CCC from transcriptomics?

- [Non-spatial Data](https://liana-py.readthedocs.io/en/latest/notebooks/sc_multi.html#Metabolite-mediated-CCC-from-Transcriptomics-Data)

## API

For further information please check LIANA's [API documentation](https://liana-py.readthedocs.io/en/latest/api.html).

## Cite LIANA+:

Dimitrov D., Schäfer P.S.L, Farr E., Rodriguez Mier P., Lobentanzer S., Badia-i-Mompel P., Dugourd A., Tanevski J., Ramirez Flores R.O. and Saez-Rodriguez J. LIANA+ provides an all-in-one framework for cell–cell communication inference. Nat Cell Biol (2024). https://doi.org/10.1038/s41556-024-01469-w

Dimitrov, D., Türei, D., Garrido-Rodriguez M., Burmedi P.L., Nagai, J.S., Boys, C., Flores, R.O.R., Kim, H., Szalai, B., Costa, I.G., Valdeolivas, A., Dugourd, A. and Saez-Rodriguez, J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat Commun 13, 3224 (2022). https://doi.org/10.1038/s41467-022-30755-0

Please also consider citing any of the methods and/or resources that were particularly relevant for your research!