scDeepCluster: Deep Clustering for Single Cell RNA-Seq Data
Tian et al.
scDeepCluster, is a single-cell model-based deep embedded clustering method, which simultaneously learns feature representation and clustering via explicit modelling of scRNA-seq data generation. Based on testing extensive simulated data and real datasets from four representative single-cell sequencing platforms, scDeepCluster outperformed state-of-the-art methods under various clustering performance metrics and exhibited improved scalability, with running time increasing linearly with sample size. Its accuracy and efficiency make scDeepCluster a promising algorithm for clustering large-scale scRNA-seq data.
Example use case: exploring cell heterogeneity and diversity in cancer research
Technology: Autoencoders
Citation:
Tian, T., Wan, J., Song, Q. et al. Clustering single-cell RNA-seq data with a model-based deep learning approach. Nat Mach Intell 1, 191–198 (2019). https://doi.org/10.1038/s42256-019-0037-0
Released: Jun-27-2022
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