Reproducible analysis of disease space via principal components using the novel R package syndRomics

  1. Abel Torres Espín  Is a corresponding author
  2. Austin Chou
  3. Russell Huie
  4. Nikolaos Kyritsis
  5. Pavan S Upadhyayula
  6. Adam Ferguson  Is a corresponding author
  1. University of California, San Francisco, United States
  2. University of California, San Diego, United States

Abstract

Biomedical data are usually analyzed at the univariate level, focused on a single primary outcome measure to provide insight into systems biology, complex disease states, and precision medicine opportunities. More broadly, these complex biological and disease states can be detected as common factors emerging from the relationships among measured variables using multivariate approaches. 'Syndromics' refers to an analytical framework for measuring disease states using principal component analysis and related multivariate statistics as primary tools for extracting underlying disease patterns. A key part of the syndromic workflow is the interpretation, the visualization, and the study of robustness of the main components that characterize the disease space. We present a new software package, syndRomics, an open-source R package with utility for component visualization, interpretation, and stability for syndromic analysis. We document the implementation of syndRomics and illustrate the use of the package in case studies of neurological trauma data.

Data availability

This work used already available data at the Open Data Commons for Spinal Cord Injury (odc-sci.org). The data comes from ODC-SCI:26 dataset 474 (https://scicrunch.org/odc-sci/about/odc-sci_26).

The following previously published data sets were used

Article and author information

Author details

  1. Abel Torres Espín

    Neurological Surgery, University of California, San Francisco, San Francisco, United States
    For correspondence
    abel.torresespin@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Austin Chou

    Neurological Surgery, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Russell Huie

    Neurological Surgery, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Nikolaos Kyritsis

    Neurological Surgery, University of California, San Francisco, San Francsico, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Pavan S Upadhyayula

    School of Medicine, University of California, San Diego, San Diego, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Adam Ferguson

    Neurological Surgery, University of California, San Francisco, San Francisco, United States
    For correspondence
    adam.ferguson@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7102-1608

Funding

National Institute of Health (NS106899)

  • Adam Ferguson

National Institute of Health (NS088475)

  • Adam Ferguson

Veterans Affairs (1I01RX002245)

  • Adam Ferguson

Veterans Affairs (I01RX002787)

  • Adam Ferguson

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Mone Zaidi, Icahn School of Medicine at Mount Sinai, United States

Publication history

  1. Received: August 5, 2020
  2. Accepted: January 13, 2021
  3. Accepted Manuscript published: January 14, 2021 (version 1)
  4. Version of Record published: February 2, 2021 (version 2)

Copyright

© 2021, Torres Espín et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Abel Torres Espín
  2. Austin Chou
  3. Russell Huie
  4. Nikolaos Kyritsis
  5. Pavan S Upadhyayula
  6. Adam Ferguson
(2021)
Reproducible analysis of disease space via principal components using the novel R package syndRomics
eLife 10:e61812.
https://doi.org/10.7554/eLife.61812

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