SHARP: hyperfast and accurate processing of single-cell RNA-seq data via ensemble random projection
- 1Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA;
- 2Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA;
- 3Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA;
- 4Biotech Research and Innovation Centre (BRIC), University of Copenhagen, 2200 Copenhagen North, Denmark;
- 5Novo Nordisk Foundation Center for Stem Cell Biology, DanStem, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen North, Denmark
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.
Footnotes
-
[Supplemental material is available for this article.]
-
Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.254557.119.
- Received July 10, 2019.
- Accepted January 23, 2020.
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
