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

CellView: Interactive exploration of high dimensional single cell RNA-seq data

Mohan T. Bolisetty, Michael L. Stitzel, Paul Robson
doi: https://doi.org/10.1101/123810
Mohan T. Bolisetty
1The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael L. Stitzel
1The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA;
2Institute for Systems Genomics, University of Connecticut, Farmington, Connecticut 06032, USA;
3Department of Genetics & Genome Sciences, University of Connecticut, Farmington, Connecticut 06032, USA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Paul Robson
1The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA;
2Institute for Systems Genomics, University of Connecticut, Farmington, Connecticut 06032, USA;
3Department of Genetics & Genome Sciences, University of Connecticut, Farmington, Connecticut 06032, USA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Advances in high-throughput single cell transcriptomics technologies have revolutionized the study of complex tissues. It is now possible to measure gene expression across thousands of individual cells to define cell types and states. While powerful computational and statistical frameworks are emerging to analyze these complex datasets, a gap exists between this data and a biologist’s insight. The CellView web application fills this gap by providing easy and intuitive exploration of single cell transcriptome data.

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 April 04, 2017.
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.
CellView: Interactive exploration of high dimensional single cell RNA-seq 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
CellView: Interactive exploration of high dimensional single cell RNA-seq data
Mohan T. Bolisetty, Michael L. Stitzel, Paul Robson
bioRxiv 123810; doi: https://doi.org/10.1101/123810
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
CellView: Interactive exploration of high dimensional single cell RNA-seq data
Mohan T. Bolisetty, Michael L. Stitzel, Paul Robson
bioRxiv 123810; doi: https://doi.org/10.1101/123810

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 (4094)
  • Biochemistry (8784)
  • Bioengineering (6490)
  • Bioinformatics (23377)
  • Biophysics (11761)
  • Cancer Biology (9164)
  • Cell Biology (13267)
  • Clinical Trials (138)
  • Developmental Biology (7420)
  • Ecology (11380)
  • Epidemiology (2066)
  • Evolutionary Biology (15110)
  • Genetics (10408)
  • Genomics (14017)
  • Immunology (9133)
  • Microbiology (22086)
  • Molecular Biology (8792)
  • Neuroscience (47417)
  • Paleontology (350)
  • Pathology (1421)
  • Pharmacology and Toxicology (2483)
  • Physiology (3710)
  • Plant Biology (8060)
  • Scientific Communication and Education (1433)
  • Synthetic Biology (2213)
  • Systems Biology (6019)
  • Zoology (1251)