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Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning
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https://doi.org/10.1038/s41592-019-0353-7Abstract
Recent advances in large-scale single-cell RNA-seq enable fine-grained characterization of phenotypically distinct cellular states in heterogeneous tissues. We present scScope, a scalable deep-learning-based approach that can accurately and rapidly identify cell-type composition from millions of noisy single-cell gene-expression profiles.
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