Measuring sequencer size bias using REcount: A novel method for highly accurate Illumina sequencing-based quantification

Daryl M. Gohl, Alessandro Magli, John Garbe, Aaron Becker, Darrell M. Johnson, Shea Anderson, Benjamin Auch, Bradley Billstein, Elyse Froehling, Shana L. McDevitt, Kenneth B. Beckman

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant quantitative error. We describe REcount, a novel PCR-free direct counting method. Comparing measurements of defined plasmid pools to droplet digital PCR data demonstrates that REcount is highly accurate and reproducible. We use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencers and illustrate the impacts on interpretation of next-generation sequencing data and the economics of data generation.

Original languageEnglish (US)
Article number85
JournalGenome biology
Volume20
Issue number1
DOIs
StatePublished - Apr 29 2019

Bibliographical note

Publisher Copyright:
© 2019 The Author(s).

Keywords

  • ATAC-Seq
  • DNA library preparation
  • Genotyping by sequencing
  • Illumina
  • Next-generation sequencing
  • PCR-free
  • RAD-Seq
  • RNA-Seq
  • Size bias

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