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Projected t-SNE for batch correction.

Publication ,  Journal Article
Aliverti, E; Tilson, JL; Filer, DL; Babcock, B; Colaneri, A; Ocasio, J; Gershon, TR; Wilhelmsen, KC; Dunson, DB
Published in: Bioinformatics (Oxford, England)
June 2020

Low-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects. The proposed algorithm can therefore significantly aid visualization of high-dimensional data.The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumours.Source code implementing the proposed approach is available as an R package at https://github.com/emanuelealiverti/BC_tSNE, including a tutorial to reproduce the simulation studies.aliverti@stat.unipd.it.

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Published In

Bioinformatics (Oxford, England)

DOI

EISSN

1367-4811

ISSN

1367-4803

Publication Date

June 2020

Volume

36

Issue

11

Start / End Page

3522 / 3527

Related Subject Headings

  • Software
  • Mice
  • Gene Expression Profiling
  • Gene Expression
  • Endothelial Cells
  • Bioinformatics
  • Animals
  • Algorithms
  • 49 Mathematical sciences
  • 46 Information and computing sciences
 

Citation

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Aliverti, E., Tilson, J. L., Filer, D. L., Babcock, B., Colaneri, A., Ocasio, J., … Dunson, D. B. (2020). Projected t-SNE for batch correction. Bioinformatics (Oxford, England), 36(11), 3522–3527. https://doi.org/10.1093/bioinformatics/btaa189
Aliverti, Emanuele, Jeffrey L. Tilson, Dayne L. Filer, Benjamin Babcock, Alejandro Colaneri, Jennifer Ocasio, Timothy R. Gershon, Kirk C. Wilhelmsen, and David B. Dunson. “Projected t-SNE for batch correction.Bioinformatics (Oxford, England) 36, no. 11 (June 2020): 3522–27. https://doi.org/10.1093/bioinformatics/btaa189.
Aliverti E, Tilson JL, Filer DL, Babcock B, Colaneri A, Ocasio J, et al. Projected t-SNE for batch correction. Bioinformatics (Oxford, England). 2020 Jun;36(11):3522–7.
Aliverti, Emanuele, et al. “Projected t-SNE for batch correction.Bioinformatics (Oxford, England), vol. 36, no. 11, June 2020, pp. 3522–27. Epmc, doi:10.1093/bioinformatics/btaa189.
Aliverti E, Tilson JL, Filer DL, Babcock B, Colaneri A, Ocasio J, Gershon TR, Wilhelmsen KC, Dunson DB. Projected t-SNE for batch correction. Bioinformatics (Oxford, England). 2020 Jun;36(11):3522–3527.

Published In

Bioinformatics (Oxford, England)

DOI

EISSN

1367-4811

ISSN

1367-4803

Publication Date

June 2020

Volume

36

Issue

11

Start / End Page

3522 / 3527

Related Subject Headings

  • Software
  • Mice
  • Gene Expression Profiling
  • Gene Expression
  • Endothelial Cells
  • Bioinformatics
  • Animals
  • Algorithms
  • 49 Mathematical sciences
  • 46 Information and computing sciences