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.
Installation and Usage
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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.