Abstract

 

We present CALISTA (Clustering and Lineage Inference in Single-Cell Transcriptional Analysis), a numerically efficient and highly scalable toolbox for an end-to-end analysis of single-cell transcriptomic profiles. CALISTA includes four essential single-cell analyses for cell differentiation studies, including single-cell clustering, reconstruction of cell lineage specification, transition gene identification, and cell pseudotime ordering. These analyses can be applied individually or in a pipeline.

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Installation and Usage

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Please visit our Installation and Tutorials pages for detailed instructions about how to use CALISTA.

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References

 

Please click here. 

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Note

 

If you find problems with the software or errors in the documentation, report the issue in our Github repository. If you would like to contribute please contact the authors.

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