Nov 4, 2018

SHARP: Single-cell RNA-seq Hyper-fast and Accurate Processing via Ensemble Random Projection

BioRxiv : the Preprint Server for Biology
Shibiao WanKyoung Jae Won


To process large-scale single-cell RNA-sequencing (scRNA-seq) data effectively without excessive distortion during dimension reduction, we present SHARP, an ensemble random projection-based algorithm which is scalable to clustering 10 million cells. Comprehensive benchmarking tests on 17 public scRNA-seq datasets demonstrate that SHARP outperforms existing methods in terms of speed and accuracy. Particularly, for large-size datasets (>40,000 cells), SHARP's running speed far excels other competitors while maintaining high clustering accuracy and robustness. To the best of our knowledge, SHARP is the only R-based tool that is scalable to clustering scRNA-seq data with 10 million cells.

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Mentioned in this Paper

Sequence Determinations, RNA
Sequence Determinations
SPEN protein, human
RNA, Small Cytoplasmic
Reduction - Action
Abnormal Shape
Gene Feature

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