LIANA - a LIgand-receptor ANalysis frAmework
Project description
LIANA: a LIgand-receptor ANalysis frAmework
LIANA is a Ligand-Receptor inference framework that enables the use of any LR method with any resource. This is its faster and memory efficient Python implementation, an R version is also available here.
For further information please check LIANA's documentation, and also tutorial.
Install LIANA
Install liana's stable version:
pip install liana
Install liana's most up-to-date version:
pip install git+https://github.com/saezlab/liana-py
Methods
The methods implemented in this repository are:
- CellPhoneDBv2
- NATMI
- Connectome
- SingleCellSignalR
- CellChat (+)
- 1-vs-rest expression
LogFC
score Geometric Mean
- ligand-receptor geometric mean with pvalues obtained via the permutation approach implemented by CellPhoneDBv2rank_aggregate
of the predictions calculated with the RobustRankAggregate method
(+) A resource-independent adaptation of the CellChat LR inference functions.
Ligand-Receptor Resources
The following CCC resources are accessible via this pipeline:
- Consensus ($)
- CellCall
- CellChatDB
- CellPhoneDB
- Ramilowski2015
- Baccin2019
- LRdb
- Kiroauc2010
- ICELLNET
- iTALK
- EMBRACE
- HPMR
- Guide2Pharma
- ConnectomeDB2020
- CellTalkDB
- MouseConsensus (#)
($) LIANA's default Consensus
resource was generated from several expert-curated resources,
filtered to additional quality control steps including literature support, complex re-union/consensus,
and localisation.
(#) Consensus Resource converted to murine homologs.
Cite LIANA:
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 Also, if you use the OmniPath CCC Resource for your analysis, please cite:
Türei, D., Valdeolivas, A., Gul, L., Palacio‐Escat, N., Klein, M., Ivanova, O., Ölbei, M., Gábor, A., Theis, F., Módos, D. and Korcsmáros, T., 2021. Integrated intra‐and intercellular signaling knowledge for multicellular omics analysis. Molecular systems biology, 17(3), p.e9923. https://doi.org/10.15252/msb.20209923
Similarly, please consider citing any of the methods and/or resources implemented in liana, that were particularly relevant for your research!
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