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Detecting large deletions at base pair level by combining split read and paired read data.

Matthew Hayes1, Jeremy S Pearson2

  • 1Xavier University of Louisiana, 1 Drexel Dr, New Orleans, 70125, LA, USA. mhayes5@xula.edu.

BMC Bioinformatics
|October 27, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces Pegasus, a new algorithm for precisely locating genomic deletions and their breakpoints using next-generation sequencing data. Pegasus accurately identifies structural variants, aiding in cancer research and treatment.

Keywords:
DeletionsSequencingStructural variant

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Area of Science:

  • Genomics and Bioinformatics
  • Cancer Research
  • Molecular Biology

Background:

  • Genomic structural variants (SVs), particularly deletions, are crucial in cancer development by creating oncogenic fusions or inactivating tumor suppressors.
  • Accurate detection and high-resolution breakpoint mapping of deletions are clinically significant for disease treatment and understanding tumorigenesis.
  • Existing methods for SV detection require improvement in precision for clinical applications.

Purpose of the Study:

  • To develop and validate a novel computational method for precise, base-pair level detection of genomic deletions using next-generation sequencing (NGS) data.
  • To generalize a previously established translocation detection framework for deletion breakpoint identification.
  • To assess the accuracy and performance of the new algorithm against existing methods.

Main Methods:

  • Adapted a framework from a translocation-locating algorithm to specifically identify deletions.
  • Utilized abnormally mapped read pairs from NGS data to pinpoint potential deletion regions.
  • Employed split read mapping to determine precise deletion breakpoints at base-pair resolution.

Main Results:

  • The developed algorithm, Pegasus, demonstrated high accuracy in predicting the number, type, and breakpoints of biologically validated structural variants (SVs).
  • Performance was evaluated on both a primary prostate cancer dataset and a simulated dataset, confirming its predictive power.
  • Pegasus outperformed two existing algorithms in predicting precise deletion breakpoints, a critical factor for clinical relevance.

Conclusions:

  • Pegasus accurately identifies deletion breakpoints, offering a valuable tool for cancer genomics research.
  • Future development should incorporate germline variant filtering and heterozygous deletion detection capabilities.
  • The source code for Pegasus is publicly available for download.