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

A multi-view model for relative and absolute microbial abundances

Brian D. Williamson, James P. Hughes, View ORCID ProfileAmy D. Willis
doi: https://doi.org/10.1101/761486
Brian D. Williamson
Department of Biostatistics, University of Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James P. Hughes
Department of Biostatistics, University of Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amy D. Willis
Department of Biostatistics, University of Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Amy D. Willis
  • For correspondence: adwillis@uw.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The absolute abundance of bacterial taxa in human host-associated environments play a critical role in reproductive and gastrointestinal health. However, obtaining the absolute abundance of many bacterial species is typically prohibitively expensive. In contrast, relative abundance data for many species is comparatively cheap and easy to collect (e.g., with universal primers for the 16S rRNA gene). In this paper, we propose a method to jointly model relative abundance data for many taxa and absolute abundance data for a subset of taxa. Our method provides point and interval estimates for the absolute abundance of all taxa. Crucially, our proposal accounts for differences in the efficiency of taxon detection in the relative and absolute abundance data. We show that modeling taxon-specific efficiencies substantially reduces the estimation error for absolute abundance, and controls the coverage of interval estimators. We demonstrate the performance of our proposed method via a simulation study, a sensitivity study where we jackknife the taxa with observed absolute abundances, and a study of women with bacterial vaginosis.

Footnotes

  • https://github.com/statdivlab/paramedic/

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-ND 4.0 International license.
Back to top
PreviousNext
Posted September 08, 2019.
Download PDF
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.
A multi-view model for relative and absolute microbial abundances
(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
A multi-view model for relative and absolute microbial abundances
Brian D. Williamson, James P. Hughes, Amy D. Willis
bioRxiv 761486; doi: https://doi.org/10.1101/761486
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A multi-view model for relative and absolute microbial abundances
Brian D. Williamson, James P. Hughes, Amy D. Willis
bioRxiv 761486; doi: https://doi.org/10.1101/761486

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

  • Genomics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4684)
  • Biochemistry (10361)
  • Bioengineering (7675)
  • Bioinformatics (26337)
  • Biophysics (13529)
  • Cancer Biology (10686)
  • Cell Biology (15440)
  • Clinical Trials (138)
  • Developmental Biology (8497)
  • Ecology (12821)
  • Epidemiology (2067)
  • Evolutionary Biology (16862)
  • Genetics (11399)
  • Genomics (15478)
  • Immunology (10617)
  • Microbiology (25219)
  • Molecular Biology (10223)
  • Neuroscience (54473)
  • Paleontology (401)
  • Pathology (1668)
  • Pharmacology and Toxicology (2897)
  • Physiology (4342)
  • Plant Biology (9247)
  • Scientific Communication and Education (1586)
  • Synthetic Biology (2558)
  • Systems Biology (6781)
  • Zoology (1466)