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

Comparative analysis of single-cell RNA-sequencing methods

Christoph Ziegenhain, Swati Parekh, Beate Vieth, Martha Smets, Heinrich Leonhardt, Ines Hellmann, Wolfgang Enard
doi: https://doi.org/10.1101/035758
Christoph Ziegenhain
1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Swati Parekh
1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Beate Vieth
1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martha Smets
2Human Biology & Bioimaging, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Heinrich Leonhardt
2Human Biology & Bioimaging, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ines Hellmann
1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wolfgang Enard
1Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, 82152 Martinsried, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: enard@bio.lmu.de
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Single-cell mRNA sequencing (scRNA-seq) allows to profile heterogeneous cell populations, offering exciting possibilities to tackle a variety of biological and medical questions. A range of methods has been recently developed, making it necessary to systematically compare their sensitivity, accuracy, precision and cost-efficiency. Here, we have generated and analyzed scRNA-seq data from 479 mouse ES cells and spike-in controls that were prepared with four different methods in two independent replicates each. We compare their sensitivity by the number of detected genes and by the efficiency with which they capture spiked-in mRNAs, their accuracy by correlating spiked-in mRNA concentrations with estimated expression levels, their precision by power simulations and variance decomposition and their efficiency by their costs to reach a given amount of power. While accuracy is similar for all methods, we find that Smart-seq on a microfluidic platform is the most sensitive method, CEL-seq is the most precise method and SCRB-seq and Drop-seq are the most efficient methods. Our analysis provides a solid basis to choose among four available scRNA-seq methods and to benchmark future method development.

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 January 05, 2016.
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.
Comparative analysis of single-cell RNA-sequencing methods
(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
Comparative analysis of single-cell RNA-sequencing methods
Christoph Ziegenhain, Swati Parekh, Beate Vieth, Martha Smets, Heinrich Leonhardt, Ines Hellmann, Wolfgang Enard
bioRxiv 035758; doi: https://doi.org/10.1101/035758
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Comparative analysis of single-cell RNA-sequencing methods
Christoph Ziegenhain, Swati Parekh, Beate Vieth, Martha Smets, Heinrich Leonhardt, Ines Hellmann, Wolfgang Enard
bioRxiv 035758; doi: https://doi.org/10.1101/035758

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 (4395)
  • Biochemistry (9619)
  • Bioengineering (7111)
  • Bioinformatics (24915)
  • Biophysics (12642)
  • Cancer Biology (9980)
  • Cell Biology (14388)
  • Clinical Trials (138)
  • Developmental Biology (7977)
  • Ecology (12135)
  • Epidemiology (2067)
  • Evolutionary Biology (16010)
  • Genetics (10938)
  • Genomics (14764)
  • Immunology (9889)
  • Microbiology (23719)
  • Molecular Biology (9493)
  • Neuroscience (50969)
  • Paleontology (370)
  • Pathology (1544)
  • Pharmacology and Toxicology (2688)
  • Physiology (4031)
  • Plant Biology (8685)
  • Scientific Communication and Education (1512)
  • Synthetic Biology (2403)
  • Systems Biology (6446)
  • Zoology (1346)