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

A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level

Florian Mair, Jami R. Erickson, Valentin Voillet, Yannick Simoni, Timothy Bi, Aaron J. Tyznik, Jody Martin, Raphael Gottardo, Evan W. Newell, Martin Prlic
doi: https://doi.org/10.1101/700534
Florian Mair
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jami R. Erickson
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Valentin Voillet
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yannick Simoni
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Timothy Bi
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Aaron J. Tyznik
BD Biosciences, La Jolla, CA 92037, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jody Martin
BD Biosciences, La Jolla, CA 92037, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Raphael Gottardo
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USAFred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA 98109, USA; Department of Statistics, University of Washington, Seattle, WA 98195, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rgottard@fredhutch.org enewell@fredhutch.org mprlic@fredhutch.org
Evan W. Newell
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rgottard@fredhutch.org enewell@fredhutch.org mprlic@fredhutch.org
Martin Prlic
Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USADepartment of Global Health and Department of Immunology, University of Washington, Seattle, WA 98195
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rgottard@fredhutch.org enewell@fredhutch.org mprlic@fredhutch.org
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/700534
History 
  • July 14, 2019.
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.

Author Information

  1. Florian Mair*,1,
  2. Jami R. Erickson*,1,
  3. Valentin Voillet1,
  4. Yannick Simoni1,
  5. Timothy Bi1,
  6. Aaron J. Tyznik2,
  7. Jody Martin2,
  8. Raphael Gottardo1,3,#,
  9. Evan W. Newell1,# and
  10. Martin Prlic1,4,#
  1. 1Fred Hutchinson Cancer Research Center, Vaccine and Infectious Disease Division, Seattle, WA 98109, USA
  2. 2BD Biosciences, La Jolla, CA 92037, USA
  3. 3Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Seattle, WA 98109, USA; Department of Statistics, University of Washington, Seattle, WA 98195, USA
  4. 4Department of Global Health and Department of Immunology, University of Washington, Seattle, WA 98195
  1. ↵#Corresponding authors: Raphael Gottardo: rgottard{at}fredhutch.org, Evan Newell: enewell{at}fredhutch.org, Martin Prlic: mprlic{at}fredhutch.org
  1. ↵* These authors contributed equally

Back to top
PreviousNext
Posted July 14, 2019.
Download PDF
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 targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level
Florian Mair, Jami R. Erickson, Valentin Voillet, Yannick Simoni, Timothy Bi, Aaron J. Tyznik, Jody Martin, Raphael Gottardo, Evan W. Newell, Martin Prlic
bioRxiv 700534; doi: https://doi.org/10.1101/700534
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level
Florian Mair, Jami R. Erickson, Valentin Voillet, Yannick Simoni, Timothy Bi, Aaron J. Tyznik, Jody Martin, Raphael Gottardo, Evan W. Newell, Martin Prlic
bioRxiv 700534; doi: https://doi.org/10.1101/700534

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

  • Immunology
Subject Areas
All Articles
  • Animal Behavior and Cognition (1519)
  • Biochemistry (2473)
  • Bioengineering (1727)
  • Bioinformatics (9648)
  • Biophysics (3884)
  • Cancer Biology (2961)
  • Cell Biology (4173)
  • Clinical Trials (135)
  • Developmental Biology (2620)
  • Ecology (4084)
  • Epidemiology (2031)
  • Evolutionary Biology (6868)
  • Genetics (5195)
  • Genomics (6482)
  • Immunology (2176)
  • Microbiology (6909)
  • Molecular Biology (2746)
  • Neuroscience (17197)
  • Paleontology (125)
  • Pathology (425)
  • Pharmacology and Toxicology (703)
  • Physiology (1050)
  • Plant Biology (2478)
  • Scientific Communication and Education (642)
  • Synthetic Biology (828)
  • Systems Biology (2680)
  • Zoology (429)