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

Accurate, fast, and model-aware transcript expression quantification with Salmon

Rob Patro, Geet Duggal, Carl Kingsford
doi: https://doi.org/10.1101/021592
Rob Patro
1Department of Computer Science, Stony Brook University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Geet Duggal
2Department of Computational Biology, Carnegie Mellon University
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Carl Kingsford
2Department of Computational Biology, Carnegie Mellon University
  • 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

Existing methods for quantifying transcript abundance require a fundamental compromise: either use high quality read alignments and experiment-specific models or sacrifice them for speed. We introduce Salmon, a quantification method that overcomes this restriction by combining a novel ‘lightweight’ alignment procedure with a streaming parallel inference algorithm and a feature-rich bias model. These innovations yield both exceptional accuracy and order-of-magnitude speed benefits over traditional alignment-based methods.

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 October 03, 2015.
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.
Accurate, fast, and model-aware transcript expression quantification with Salmon
(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
Accurate, fast, and model-aware transcript expression quantification with Salmon
Rob Patro, Geet Duggal, Carl Kingsford
bioRxiv 021592; doi: https://doi.org/10.1101/021592
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Accurate, fast, and model-aware transcript expression quantification with Salmon
Rob Patro, Geet Duggal, Carl Kingsford
bioRxiv 021592; doi: https://doi.org/10.1101/021592

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 (3516)
  • Biochemistry (7373)
  • Bioengineering (5353)
  • Bioinformatics (20340)
  • Biophysics (10054)
  • Cancer Biology (7787)
  • Cell Biology (11357)
  • Clinical Trials (138)
  • Developmental Biology (6456)
  • Ecology (9993)
  • Epidemiology (2065)
  • Evolutionary Biology (13367)
  • Genetics (9378)
  • Genomics (12623)
  • Immunology (7732)
  • Microbiology (19122)
  • Molecular Biology (7482)
  • Neuroscience (41179)
  • Paleontology (301)
  • Pathology (1236)
  • Pharmacology and Toxicology (2144)
  • Physiology (3186)
  • Plant Biology (6885)
  • Scientific Communication and Education (1277)
  • Synthetic Biology (1901)
  • Systems Biology (5331)
  • Zoology (1091)