Visualization and cellular hierarchy inference of single-cell data using SPADE.
High-throughput single-cell technologies provide an unprecedented view into cellular heterogeneity, yet they pose new challenges in data analysis and interpretation. In this protocol, we describe the use of Spanning-tree Progression Analysis of Density-normalized Events (SPADE), a density-based algorithm for visualizing single-cell data and enabling cellular hierarchy inference among subpopulations of similar cells. It was initially developed for flow and mass cytometry single-cell data. We describe SPADE's implementation and application using an open-source R package that runs on Mac OS X, Linux and Windows systems. A typical SPADE analysis on a 2.27-GHz processor laptop takes ∼5 min. We demonstrate the applicability of SPADE to single-cell RNA-seq data. We compare SPADE with recently developed single-cell visualization approaches based on the t-distribution stochastic neighborhood embedding (t-SNE) algorithm. We contrast the implementation and outputs of these methods for normal and malignant hematopoietic cells analyzed by mass cytometry and provide recommendations for appropriate use. Finally, we provide an integrative strategy that combines the strengths of t-SNE and SPADE to infer cellular hierarchy from high-dimensional single-cell data.
Department of Radiology, Center for Cancer Systems Biology, Stanford University, Stanford, California, USA.
Benedict
B
Anchang
Department of Radiology, Center for Cancer Systems Biology, Stanford University, Stanford, California, USA.
Tom D P
TD
Hart
Department of Pathology, School of Medicine, Stanford University, Stanford, California, USA.
Sean C
SC
Bendall
Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.
Peng
P
Qiu
Department of Microbiology and Immunology, Stanford University, Stanford, California, USA.
Zach
Z
Bjornson
Computer Systems Laboratory, Stanford University, Stanford, California, USA.
Michael
M
Linderman
Department of Microbiology and Immunology, Stanford University, Stanford, California, USA.
Garry P
GP
Nolan
Department of Radiology, Center for Cancer Systems Biology, Stanford University, Stanford, California, USA.
Sylvia K
SK
Plevritis
D000465:Algorithms; D000818:Animals; D015703:Antigens, CD / Q000032:analysis; D019337:Hematologic Neoplasms / Q000737:chemistry / Q000473:pathology; D006412:Hematopoietic Stem Cells / Q000737:chemistry / Q000473:pathology; D057166:High-Throughput Screening Assays / Q000379:methods; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D051379:Mice; D017423:Sequence Analysis, RNA / Q000379:methods*; D059010:Single-Cell Analysis / Q000379:methods*; D012984:Software; D013269:Stochastic Processes
D015703:Antigens, CD