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

Identification of transcriptional signatures for cell types from single-cell RNA-Seq

Vasilis Ntranos, Lynn Yi, Páll Melsted, Lior Pachter
doi: https://doi.org/10.1101/258566
Vasilis Ntranos
1Department of Electrical Engineering & Computer Science, UC Berkeley, Berkeley, CA
2Department of Electrical Engineering, Stanford University, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lynn Yi
3UCLA-Caltech Medical Science Training Program, Los Angeles, CA
4Division of Biology and Biological Engineering, Caltech, Pasadena, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Páll Melsted
5Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lior Pachter
4Division of Biology and Biological Engineering, Caltech, Pasadena, CA
6Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: lpachter@caltech.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Single-cell RNA-Seq makes it possible to characterize the transcriptomes of cell types and identify their transcriptional signatures via differential analysis. We present a fast and accurate method for discriminating cell types that takes advantage of the large numbers of cells that are assayed. When applied to transcript compatibility counts obtained via pseudoalignment, our approach provides a quantification-free analysis of 3’ single-cell RNA-Seq that can identify previously undetectable marker genes.

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-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted February 14, 2018.
Download PDF

Supplementary Material

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.
Identification of transcriptional signatures for cell types from single-cell RNA-Seq
(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
Identification of transcriptional signatures for cell types from single-cell RNA-Seq
Vasilis Ntranos, Lynn Yi, Páll Melsted, Lior Pachter
bioRxiv 258566; doi: https://doi.org/10.1101/258566
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Identification of transcriptional signatures for cell types from single-cell RNA-Seq
Vasilis Ntranos, Lynn Yi, Páll Melsted, Lior Pachter
bioRxiv 258566; doi: https://doi.org/10.1101/258566

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 (3586)
  • Biochemistry (7545)
  • Bioengineering (5495)
  • Bioinformatics (20732)
  • Biophysics (10294)
  • Cancer Biology (7951)
  • Cell Biology (11611)
  • Clinical Trials (138)
  • Developmental Biology (6586)
  • Ecology (10168)
  • Epidemiology (2065)
  • Evolutionary Biology (13580)
  • Genetics (9521)
  • Genomics (12817)
  • Immunology (7906)
  • Microbiology (19503)
  • Molecular Biology (7641)
  • Neuroscience (41982)
  • Paleontology (307)
  • Pathology (1254)
  • Pharmacology and Toxicology (2192)
  • Physiology (3259)
  • Plant Biology (7025)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1947)
  • Systems Biology (5419)
  • Zoology (1113)