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Submodular sketches of single-cell RNA-seq measurements

Authors:

Jeffrey Bilmes,

William Stafford NobleAuthors Info & Claims

BCB '20: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

Article No.: 61, Pages 1 - 6

https://doi.org/10.1145/3388440.3412409

Published: 10 November 2020 Publication History

Abstract

Single-cell RNA-seq (scRNA-seq) datasets now routinely profile tens of thousands to millions of cells. These data are invaluable for finding important subpopulations of cells and for closely studying the mechanics of gene expression. However, as these datasets become larger, they become more difficult to analyze. Analyzing and sharing massive single-cell RNA-seq datasets can be facilitated by creating a "sketch" of the data---a selected subset of cells that accurately represent the full dataset. In this work, we use an existing benchmark to demonstrate the utility of submodular optimization in efficiently creating high quality sketches of scRNA-seq data.

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Cited By

Zelig AKariti HKaplan N(2023)KMD clustering: robust general-purpose clustering of biological dataCommunications Biology10.1038/s42003-023-05480-z6:1Online publication date: 2-Nov-2023
https://doi.org/10.1038/s42003-023-05480-z
Baker DDyjack NBraverman VHicks SLangmead BJiang HHuang XZhang J(2021)Fast and memory-efficient scRNA-seq k-means clustering with various distancesProceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3459930.3469523(1-8)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1145/3459930.3469523

Index Terms

Submodular sketches of single-cell RNA-seq measurements
1. Applied computing
  1. Life and medical sciences
    1. Computational biology
      1. Computational genomics

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cover image ACM Conferences

BCB '20: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

September 2020

193 pages

ISBN:9781450379649

DOI:10.1145/3388440

Copyright © 2020 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGBio: ACM Special Interest Group on Bioinformatics

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Association for Computing Machinery

New York, NY, United States

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Published: 10 November 2020

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National Institutes of Health

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BCB '20

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BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

September 21 - 24, 2020

Virtual Event, USA

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Cited By

Zelig AKariti HKaplan N(2023)KMD clustering: robust general-purpose clustering of biological dataCommunications Biology10.1038/s42003-023-05480-z6:1Online publication date: 2-Nov-2023
https://doi.org/10.1038/s42003-023-05480-z
Baker DDyjack NBraverman VHicks SLangmead BJiang HHuang XZhang J(2021)Fast and memory-efficient scRNA-seq k-means clustering with various distancesProceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3459930.3469523(1-8)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1145/3459930.3469523

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