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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Identification and correction of systematic error in high-throughput sequence data.

Frazer Meacham1, Dario Boffelli, Joseph Dhahbi

  • 1Department of Mathematics, University of California, Berkeley, 970 Evans Hall #3840, Berkeley, CA 94720, USA.

BMC Bioinformatics
|November 22, 2011
PubMed
Summary

Systematic errors in DNA sequencing reads can be mistaken for genetic variations. A new classifier identifies and corrects these errors, improving high-throughput sequencing data accuracy.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • DNA sequencing technologies inherently produce base-call errors, impacting biological interpretations.
  • Next-generation sequencing, while cost-effective, exhibits increased error rates, including position- and sequence-specific errors.
  • A novel type of systematic error, characterized by localized error accumulations, has been identified.

Purpose of the Study:

  • To characterize and describe a new type of systematic error in DNA sequencing data.
  • To develop a method for distinguishing systematic errors from true heterozygous sites.
  • To create a tool for identifying and correcting systematic errors in sequencing reads.

Main Methods:

  • Utilized overlapping paired reads from high-coverage data to analyze systematic errors.
  • Developed a classifier to differentiate systematic errors from heterozygous sites, accommodating varying allele frequencies.
  • Applied motif identification at error sites to aid in classification.

Main Results:

  • Systematic errors occur at a frequency of approximately 1 in 1000 base pairs and are highly reproducible.
  • Identified specific sequence motifs associated with systematic error sites.
  • Demonstrated the classifier's ability to distinguish systematic errors from heterozygous sites, even in RNA-Seq data.

Conclusions:

  • Systematic errors can be erroneously interpreted as heterozygous sites or single nucleotide polymorphisms (SNPs).
  • These errors pose significant challenges in low-coverage experiments and allele-specific expression analyses.
  • The developed SysCall program effectively identifies and corrects systematic errors, crucial for accurate high-throughput sequencing data interpretation.