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

INC-Seq: Accurate single molecule reads using nanopore sequencing

Chenhao Li, Kern Rei Chng, Esther Jia Hui Boey, Amanda Hui Qi Ng, Andreas Wilm, Niranjan Nagarajan
doi: https://doi.org/10.1101/038042
Chenhao Li
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kern Rei Chng
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Esther Jia Hui Boey
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amanda Hui Qi Ng
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andreas Wilm
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Niranjan Nagarajan
1Genome Institute of Singapore, Singapore 138672, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: nagarajann@gis.a-star.edu.sg
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Nanopore sequencing provides a rapid, cheap and portable real-time sequencing platform with the potential to revolutionize genomics. Several applications, including RNA-seq, haplotype sequencing and 16S sequencing, are however limited by its relatively high single read error rate (>10%). We present INC-Seq (Intramolecular-ligated Nanopore Consensus Sequencing) as a strategy for obtaining long and accurate nanopore reads starting with low input DNA. Applying INC-Seq for 16S rRNA based bacterial profiling generated full-length amplicon sequences with median accuracy >97%. INC-Seq reads enable accurate species-level classification, identification of species at 0.1% abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.

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 27, 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.
INC-Seq: Accurate single molecule reads using nanopore sequencing
(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
INC-Seq: Accurate single molecule reads using nanopore sequencing
Chenhao Li, Kern Rei Chng, Esther Jia Hui Boey, Amanda Hui Qi Ng, Andreas Wilm, Niranjan Nagarajan
bioRxiv 038042; doi: https://doi.org/10.1101/038042
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
INC-Seq: Accurate single molecule reads using nanopore sequencing
Chenhao Li, Kern Rei Chng, Esther Jia Hui Boey, Amanda Hui Qi Ng, Andreas Wilm, Niranjan Nagarajan
bioRxiv 038042; doi: https://doi.org/10.1101/038042

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 (2530)
  • Biochemistry (4972)
  • Bioengineering (3482)
  • Bioinformatics (15212)
  • Biophysics (6897)
  • Cancer Biology (5390)
  • Cell Biology (7738)
  • Clinical Trials (138)
  • Developmental Biology (4530)
  • Ecology (7147)
  • Epidemiology (2059)
  • Evolutionary Biology (10227)
  • Genetics (7512)
  • Genomics (9786)
  • Immunology (4844)
  • Microbiology (13215)
  • Molecular Biology (5138)
  • Neuroscience (29435)
  • Paleontology (203)
  • Pathology (837)
  • Pharmacology and Toxicology (1463)
  • Physiology (2138)
  • Plant Biology (4748)
  • Scientific Communication and Education (1013)
  • Synthetic Biology (1338)
  • Systems Biology (4012)
  • Zoology (768)