Reference health
The art of using t-SNE for single-cell transcriptomics
46/46 checkable references clean · checked 2026-07-25
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
6 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 46 checked references that resolve
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Shared and distinct transcriptomic cell types across neocortical areas
resolves10.1038/s41586-018-0590-4
Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
resolves10.1016/j.cell.2018.07.028
Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
resolves10.1038/s41586-019-0969-x
The single-cell transcriptional landscape of mammalian organogenesis
resolves10.1016/j.neucom.2014.12.095
Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure
resolves10.1038/s41467-019-13055-y
Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets
resolves10.1038/s41592-018-0308-4
Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data
resolves10.1038/nbt.2594
viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
resolves10.1038/s41467-017-01689-9
Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types
resolves10.31235/osf.io/36neu
Stable Random Projection: Lightweight, General-Purpose Dimensionality Reduction for Digitized Libraries
resolves10.1016/j.neucom.2008.12.017
Quality assessment of dimensionality reduction: Rank-based criteria
resolves10.1016/j.cell.2015.05.002
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
resolves10.1016/j.cell.2016.07.054
Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics
resolves10.1371/journal.pbio.2006387
Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics
resolves10.1038/nbt.3445
Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq
resolves10.1101/671404
Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
resolves10.1523/JNEUROSCI.2899-04.2005
Pax6, Tbr2, and Tbr1 Are Expressed Sequentially by Radial Glia, Intermediate Progenitor Cells, and Postmitotic Neurons in Developing Neocortex
resolves10.1016/j.celrep.2017.12.017
Developmental Emergence of Adult Neural Stem Cells as Revealed by Single-Cell Transcriptional Profiling
resolves10.1186/s12915-018-0580-x
Identification of cell types in a mouse brain single-cell atlas using low sampling coverage
resolves10.1007/978-3-030-46150-8_8
Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations
resolves10.1016/j.cels.2018.05.017
Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks
resolves10.1038/s41467-018-04368-5
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
resolves10.1186/s13059-019-1663-x
PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells
resolves10.1109/TVCG.2016.2570755
Approximated and User Steerable tSNE for Progressive Visual Analytics
resolves10.1101/574574
Feature Selection and Dimension Reduction for Single Cell RNA-Seq based on a Multinomial Model
resolves10.1101/731877
openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding
The 6 references without a DOI — listed, not checked
no DOI — not checkedvan der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learning Res. 9, 2579–2605 (2008).
no DOI — not checkedBodt, C. D., Mulders, D., Verleysen, M., & Lee, J. A. Perplexity-free t-SNE and twice student tt-SNE. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 123–128 (2018).
no DOI — not checkedvan der Maaten, L. Accelerating t-SNE using tree-based algorithms. J. Mach. Learning Res. 15, 3221–3245 (2014).
no DOI — not checkedLinderman, G. C., Rachh, M., Hoskins, J. G., Steinerberger, S. & Kluger, Y. Efficient algorithms for t-distributed stochastic neighborhood embedding. https://arxiv.org/abs/1712.09005 (2017).
no DOI — not checkedvan der Maaten, L. Learning a parametric embedding by preserving local structure. In Proceedings of the Twelth International Conference on Artificial Intelligence and Statistics 384–391 (2009).
no DOI — not checkedHinton, G. E. & Roweis, S.T. Stochastic neighbor embedding. In Advances in Neural Information Processing Systems 857–864 (2003).
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