Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Triku: a feature selection method based on nearest neighbors for single-cell data

View ORCID ProfileAlex M. Ascensión, View ORCID ProfileOlga Ibañez-Solé, View ORCID ProfileInaki Inza, View ORCID ProfileAnder Izeta, View ORCID ProfileMarcos J. Araúzo-Bravo
doi: https://doi.org/10.1101/2021.02.12.430764
Alex M. Ascensión
1Biodonostia Health Research Institute, Computational Biology and Systems Biomedicine Group, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
2Tissue Engineering Group, Biodonostia Health Research Institute, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alex M. Ascensión
Olga Ibañez-Solé
1Biodonostia Health Research Institute, Computational Biology and Systems Biomedicine Group, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
2Tissue Engineering Group, Biodonostia Health Research Institute, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Olga Ibañez-Solé
Inaki Inza
3intelligent Systems Group, Computer Science Faculty, University of the Basque Country, Donostia-San Sebastian, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Inaki Inza
Ander Izeta
2Tissue Engineering Group, Biodonostia Health Research Institute, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ander Izeta
Marcos J. Araúzo-Bravo
1Biodonostia Health Research Institute, Computational Biology and Systems Biomedicine Group, Paseo Dr. Begiristain, s/n, 20014, Donostia-San Sebastian, Spain
4Max Planck Institute for Molecular Biomedicine, Roentgenstr. 20, 48149, Muenster, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Marcos J. Araúzo-Bravo
  • For correspondence: mararabra@yahoo.co.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

Feature selection is a relevant step in the analysis of single-cell RNA sequencing datasets. Triku is a feature selection method that favours genes defining the main cell populations. It does so by selecting genes expressed by groups of cells that are close in the nearest neighbor graph. Triku efficiently recovers cell populations present in artificial and biological benchmarking datasets, based on mutual information and silhouette coefficient measurements. Additionally, gene sets selected by triku are more likely to be related to relevant Gene Ontology terms, and contain fewer ribosomal and mitochondrial genes. Triku is available at https://gitlab.com/alexmascension/triku.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://www.gitlab.com/alexmascension/triku

  • 5 Abbreviations

    scRNA-seq
    Single-cell RNA sequencing
    FS
    Feature Selection
    FE
    Feature Extraction
    PCA
    Principal Component Analysis
    NB
    Negative Binomial
    (NMI)
    Normalized Mutual Information
    FACS
    Fluorescence Activated Cell Sorting
    GO
    Gene Ontology
    GOEA
    Gene Ontology Enrichment Analysis
    PBMC
    Peripheral Blood Mononuclear Cells
    UMAP
    Uniform Manifold Approximation and Projection
    kNN
    k-Nearest Neighbors
  • 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 4.0 International license.
    Back to top
    PreviousNext
    Posted February 13, 2021.
    Download PDF

    Supplementary Material

    Data/Code
    Email

    Thank you for your interest in spreading the word about bioRxiv.

    NOTE: Your email address is requested solely to identify you as the sender of this article.

    Enter multiple addresses on separate lines or separate them with commas.
    Triku: a feature selection method based on nearest neighbors for single-cell data
    (Your Name) has forwarded a page to you from bioRxiv
    (Your Name) thought you would like to see this page from the bioRxiv website.
    CAPTCHA
    This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
    Share
    Triku: a feature selection method based on nearest neighbors for single-cell data
    Alex M. Ascensión, Olga Ibañez-Solé, Inaki Inza, Ander Izeta, Marcos J. Araúzo-Bravo
    bioRxiv 2021.02.12.430764; doi: https://doi.org/10.1101/2021.02.12.430764
    Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
    Citation Tools
    Triku: a feature selection method based on nearest neighbors for single-cell data
    Alex M. Ascensión, Olga Ibañez-Solé, Inaki Inza, Ander Izeta, Marcos J. Araúzo-Bravo
    bioRxiv 2021.02.12.430764; doi: https://doi.org/10.1101/2021.02.12.430764

    Citation Manager Formats

    • BibTeX
    • Bookends
    • EasyBib
    • EndNote (tagged)
    • EndNote 8 (xml)
    • Medlars
    • Mendeley
    • Papers
    • RefWorks Tagged
    • Ref Manager
    • RIS
    • Zotero
    • Tweet Widget
    • Facebook Like
    • Google Plus One

    Subject Area

    • Bioinformatics
    Subject Areas
    All Articles
    • Animal Behavior and Cognition (3689)
    • Biochemistry (7789)
    • Bioengineering (5674)
    • Bioinformatics (21282)
    • Biophysics (10576)
    • Cancer Biology (8173)
    • Cell Biology (11937)
    • Clinical Trials (138)
    • Developmental Biology (6762)
    • Ecology (10401)
    • Epidemiology (2065)
    • Evolutionary Biology (13863)
    • Genetics (9708)
    • Genomics (13070)
    • Immunology (8139)
    • Microbiology (19983)
    • Molecular Biology (7842)
    • Neuroscience (43053)
    • Paleontology (319)
    • Pathology (1279)
    • Pharmacology and Toxicology (2258)
    • Physiology (3351)
    • Plant Biology (7232)
    • Scientific Communication and Education (1312)
    • Synthetic Biology (2004)
    • Systems Biology (5537)
    • Zoology (1128)