https://github.com/CABSEL/CALISTA
CALISTA: Clustering And Lineage Inference in Single Cell Transcriptional Analysis
https://github.com/CABSEL/CALISTA
network-analysis single-cell-analysis
Last synced: over 1 year ago
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CALISTA: Clustering And Lineage Inference in Single Cell Transcriptional Analysis
- Host: GitHub
- URL: https://github.com/CABSEL/CALISTA
- Owner: CABSEL
- License: bsd-3-clause
- Created: 2018-01-26T10:35:58.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-05-16T14:20:18.000Z (about 7 years ago)
- Last Synced: 2024-08-02T16:44:06.331Z (almost 2 years ago)
- Topics: network-analysis, single-cell-analysis
- Language: HTML
- Size: 102 MB
- Stars: 9
- Watchers: 5
- Forks: 2
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-single-cell - CALISTA - [R] - CALISTA provides a user-friendly toolbox for the analysis of single cell expression data. CALISTA accomplishes three major tasks: 1) Identification of cell clusters in a cell population based on single-cell gene expression data, 2) Reconstruction of lineage progression and produce transition genes, and 3) Pseudotemporal ordering of cells along any given developmental paths in the lineage progression. (Software packages / Pseudotime and trajectory inference)
README
CALISTA provides a user-friendly toolbox for the analysis of single cell expression data.
Please visit [CALISTA website](https://www.cabselab.com/calista) for more info about installation and how to run CALISTA.
## License
Redistribution and use in source and binary forms, with or without modification, are permitted provided agreeing to the BSD 3-Clause Style [License](https://github.com/CABSEL/CALISTA/blob/master/LICENSE).
## References
Papili Gao N., Hartmann T., Fang T. and Gunawan R., CALISTA: Clustering And Lineage Inference in Single Cell Transcriptional Analysis. [Abstract](https://www.biorxiv.org/content/early/2018/01/31/257550)
## Acknowledgement
This work is supported by funding from Swiss National Science Foundation.