Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data

• Published in: Nature methods Vol. 16; no. 3; pp. 243 - 245
• Main Authors: Linderman, George C., Rachh, Manas, Hoskins, Jeremy G., Steinerberger, Stefan, Kluger, Yuval
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.03.2019; Nature Publishing Group
• Subjects: 631/114/1305; 631/114/1386; 631/114/794; Algorithms; Animals; Base Sequence; Bioinformatics; Biological Microscopy; Biological Techniques; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Brief Communication; Computational Biology - methods; Embedding; Gene expression; Gene Expression Profiling - methods; Gene sequencing; Genetic Markers; Interpolation; Life Sciences; Mice; Proteomics; Ribonucleic acid; RNA; RNA - genetics; Sequence Analysis, RNA - methods; Single-Cell Analysis - methods; Stochastic Processes; Visualization

t -distributed stochastic neighbor embedding (t-SNE) is widely used for visualizing single-cell RNA-sequencing (scRNA-seq) data, but it scales poorly to large datasets. We dramatically accelerate t-SNE, obviating the need for data downsampling, and hence allowing visualization of rare cell populatio...