Journal
NATURE METHODS
Volume 16, Issue 3, Pages 243-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41592-018-0308-4
Keywords
-
Categories
Funding
- NIH [F30HG010102, 1R01HG008383-01A1]
- US NIH MSTP Training Grant [T32GM007205]
- AFOSR [FA9550-16-10175]
- NSF [DMS-1763179]
- Alfred P. Sloan Foundation
Ask authors/readers for more resources
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 populations. Furthermore, we implement a heatmap-style visualization for scRNA-seq based on one-dimensional t-SNE for simultaneously visualizing the expression patterns of thousands of genes. Software is available at https://github.com/KlugerLab/FIt-SNE and https://github.com/KlugerLab/t-SNE-Heatmaps.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available