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Exploring dimension-reduced embeddings with Sleepwalk

View ORCID ProfileSvetlana Ovchinnikova, View ORCID ProfileSimon Anders
doi: https://doi.org/10.1101/603589
Svetlana Ovchinnikova
Center for Molecular Biology of the University of Heidelberg, Germany
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Simon Anders
Center for Molecular Biology of the University of Heidelberg, Germany
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  • For correspondence: sanders@fs.tum.de
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Abstract

Dimension-reduction methods, such as t-SNE or UMAP, are widely used when exploring high-dimensional data describing many entities, e.g., RNA-seq data for many single cells. However, dimension reduction is commonly prone to introducing artefacts, and we hence need means to see where a dimension-reduced embedding is a faithful representation of the local neighbourhood and where it is not.

We present Sleepwalk, a simple but powerful tool that allows the user to interactively explore an embedding, using colour to depict original or any other distances from all points to the cell under the mouse cursor. We show how this approach not only highlights distortions, but also reveals otherwise hidden characteristics of the data, and how Sleep-walk’s comparative modes help integrate multi-sample data and understand differences between embedding and preprocessing methods. Sleepwalk is a versatile and intuitive tool that unlocks the full power of dimension reduction and will be of value not only in single-cell RNA-seq but also in any other area with matrix-shaped big data.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • In this revised version, we have thoroughly expanded the discussion, now outlining the tools use cases more sharply. The software itself has changed only slightly (a few new functions added).

  • https://anders-biostat.github.io/sleepwalk/supplementary/

  • https://figshare.com/articles/Murine_cerebellum_single-cell_samples/7910483

  • https://figshare.com/articles/Intermediate_data_files_to_generate_sleepwalk_examples/7910504

  • https://github.com/anders-biostat/sleepwalk/tree/paper

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 30, 2020.
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Exploring dimension-reduced embeddings with Sleepwalk
Svetlana Ovchinnikova, Simon Anders
bioRxiv 603589; doi: https://doi.org/10.1101/603589
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Exploring dimension-reduced embeddings with Sleepwalk
Svetlana Ovchinnikova, Simon Anders
bioRxiv 603589; doi: https://doi.org/10.1101/603589

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