t-SNE statistics

Tool stats & trends

Looking to identify usage trends or leading experts?


t-SNE specifications


Unique identifier OMICS_12592
Name t-SNE
Alternative names t-distributed Stochastic Neighbor Embedding, Rtsne, Parametric t-SNE, Barnes-Hut t-SNE
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java, Javascript, MATLAB, Python, R, Julia
Parallelization CUDA
License GNU General Public License version 3.0, GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes




No version available



  • person_outline Laurens van der Maaten

Additional information

R implementation of the software is also available at: https://CRAN.R-project.org/package=Rtsne

Publications for t-distributed Stochastic Neighbor Embedding

t-SNE citations


Hematopoietic stem cells can differentiate into restricted myeloid progenitors before cell division in mice

Nat Commun
PMCID: 5954009
PMID: 29765026
DOI: 10.1038/s41467-018-04188-7

[…] .3.2, and RStudio Version 0.99.486 and version 1.0.136 (Boston, MA, USA) software. Where further required, pre-processing via a linear model to correct for confounding sampling effects was conducted. t-SNE plots were created using the R package “Rtsne”. To model the bi-modal gene expression of single cells, the Hurdle model, a semi-continuous modeling framework, was applied to pre-processed data. […]


A Cluster then label Semi supervised Learning Approach for Pathology Image Classification

Sci Rep
PMCID: 5940864
PMID: 29739993
DOI: 10.1038/s41598-018-24876-0

[…] To visualize the underlying distributions of data spaces used in this study in lower dimensions, t-distributed Stochastic Neighbor Embedding (t-SNE) was used. It is an iterative method which maps data points into lower dimensional space in such a way that the distances between points correspond to their similarity. Also, we have used Fisher […]


Model based and Model free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson’s Disease

Sci Rep
PMCID: 5940671
PMID: 29740058
DOI: 10.1038/s41598-018-24783-4

[…] e similarities and differences between the pair of standardization techniques we show 2D projections of the data in each paradigm (top and bottom) using both multidimensional scaling (MDS) (left) and t-distributed Stochastic Neighbor Embedding (tSNE), (right).Figure 7Batch effects do not represent underlying biological variability. Rather, they reflect technical sources of data variation due to ha […]


Complete genome sequence and the expression pattern of plasmids of the model ethanologen Zymomonas mobilis ZM4 and its xylose utilizing derivatives 8b and 2032

Biotechnol Biofuels
PMCID: 5930841
PMID: 29743953
DOI: 10.1186/s13068-018-1116-x

[…] RNA, non-tRNA counts mapped to the respective replicon and the total length of the non-rRNA, non-tRNA features on the replicon.The data structure was visualized using both hierarchical clustering and t-distributed stochastic neighbor embedding (t-SNE) []. For gene set enrichment analysis (GSEA), gene ontology (GO) associations were extracted from the results of InterProScan with translated plasmid […]


Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging

Nat Commun
PMCID: 5923236
PMID: 29703977
DOI: 10.1038/s41467-018-04030-0

[…] lgorithm aims to place each sample in a lower dimensional space under the constraint that the between-sample distances are preserved as much as possible. Here, we used the Matlab function, cmdscale().t-SNE: t-SNE (t-distribution Stochastic Neighboring Embedding) is an advanced dimensionality reduction technique and particularly suitable for the visualization of high-dimensional datasets. In t-SNE, […]


Characterization of germ cell differentiation in the male mouse through single cell RNA sequencing

Sci Rep
PMCID: 5916943
PMID: 29695820
DOI: 10.1038/s41598-018-24725-0

[…] resence of cell populations, and differential gene expression. The mice were virtually indistinguishable in any QC statistic and yielded identical distributions after t-stochastic neighbor embedding (t-SNE) (Supplementary Fig. ). Automated, graph-based clustering revealed 11 clusters, all of which were present in both replicates (Supplementary data Table ). In mouse 1 and 2, there were two and twe […]


Looking to check out a full list of citations?

t-SNE institution(s)
Pattern Recognition and Bioinformatics Laboratory, Delft University of Technology, Delft, The Netherlands; Department of Computer Science, University of Toronto, Toronto, ON, Canada
t-SNE funding source(s)
Supported by the Netherlands Organization for Scientific Research (NWO; Rubicon grant No. 680.50.0908) and by the EU-FP7 Network of Excellence on Social Signal Processing (SSPNet); by grants from NSERC and CFI and gifts from Google and Microsoft.

t-SNE reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review t-SNE