Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 30886411.
- Also identified by DOI 10.1038/s41592-019-0353-7 and PMC identifier 6774994.
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Abstract
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.
Medical subject headings
- Databases, Genetic
- Deep Learning
- Gene Expression Profiling
- RNA
- Single-Cell Analysis
- Transcriptome