RT Journal Article
SR Electronic
T1 Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 536730
DO 10.1101/536730
A1 Brian Hie
A1 Hyunghoon Cho
A1 Benjamin DeMeo
A1 Bryan Bryson
A1 Bonnie Berger
YR 2019
UL http://biorxiv.org/content/early/2019/01/31/536730.1.abstract
AB Large-scale single-cell RNA-sequencing (scRNA-seq) studies that profile hundreds of thousands of cells are becoming increasingly common, overwhelming existing analysis pipelines. Here, we describe how to enhance and accelerate single-cell data analysis by summarizing the transcriptomic heterogeneity within a data set using a small subset of cells, which we refer to as a geometric sketch. Our sketches provide more comprehensive visualization of transcriptional diversity, capture rare cell types with high sensitivity, and accurately reveal biological cell types via clustering. Our sketch of umbilical cord blood cells uncovers a rare subpopulation of inflammatory macrophages, which we experimentally validated in vitro. The construction of our sketches is extremely fast, which enabled us to accelerate other crucial resource-intensive tasks such as scRNA-seq data integration. We anticipate that our algorithm will become an increasingly essential step when sharing and analyzing the rapidly-growing volume of scRNA-seq data and help enable the democratization of single-cell omics.