@article{Wan01022020,
author = {Wan, Shibiao and Kim, Junil and Won, Kyoung Jae}, 
title = {SHARP: hyperfast and accurate processing of single-cell RNA-seq data via ensemble random projection},
volume = {30}, 
number = {2}, 
pages = {205-213}, 
year = {2020}, 
doi = {10.1101/gr.254557.119}, 
abstract ={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.}, 
URL = {http://genome.cshlp.org/content/30/2/205.abstract}, 
eprint = {http://genome.cshlp.org/content/30/2/205.full.pdf+html}, 
journal = {Genome Research} 
}