Dataset Information

QSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets.

ABSTRACT:

Motivation

Non-parametric dimensionality reduction techniques, such as t-distributed stochastic neighbor embedding (t-SNE), are the most frequently used methods in the exploratory analysis of single-cell datasets. Current implementations scale poorly to massive datasets and often require downsampling or interpolative approximations, which can leave less-frequent populations undiscovered and much information unexploited.

Results

We implemented a fast t-SNE package, qSNE, which uses a quasi-Newton optimizer, allowing quadratic convergence rate and automatic perplexity (level of detail) optimizer. Our results show that these improvements make qSNE significantly faster than regular t-SNE packages and enables full analysis of large datasets, such as mass cytometry data, without downsampling.

Availability and implementation

Source code and documentation are openly available at https://bitbucket.org/anthakki/qsne/.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Hakkinen A

PROVIDER: S-EPMC7755412 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

qSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets.

Häkkinen Antti A Koiranen Juha J Casado Julia J Kaipio Katja K Lehtonen Oskari O Petrucci Eleonora E Hynninen Johanna J Hietanen Sakari S Carpén Olli O Pasquini Luca L Biffoni Mauro M Lehtonen Rainer R Hautaniemi Sampsa S

Bioinformatics (Oxford, England) 20201201 20

<h4>Motivation</h4>Non-parametric dimensionality reduction techniques, such as t-distributed stochastic neighbor embedding (t-SNE), are the most frequently used methods in the exploratory analysis of single-cell datasets. Current implementations scale poorly to massive datasets and often require downsampling or interpolative approximations, which can leave less-frequent populations undiscovered and much information unexploited.<h4>Results</h4>We implemented a fast t-SNE package, qSNE, which uses ...[more]

PMID: 32663244

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