RT Journal
A1 Wan, Shibiao
A1 Kim, Junil
A1 Won, Kyoung Jae
T1 SHARP: hyperfast and accurate processing of single-cell RNA-seq data via ensemble random projection
JF Genome Research 
JO Genome Research 
YR 2020 
FD February 01 
VO 30 
IS 2 
SP 205 
OP 213 
DO 10.1101/gr.254557.119 
UL http://genome.cshlp.org/content/30/2/205.abstract 
AB 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 that is scalable to clustering 10 million cells. Comprehensive benchmarking tests on 17 public scRNA-seq data sets show that SHARP outperforms existing methods in terms of speed and accuracy. Particularly, for large-size data sets (more than 40,000 cells), SHARP runs faster than 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.