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Genome-wide somatic variant calling using localized colored de Bruijn graphs.

Giuseppe Narzisi1, André Corvelo2, Kanika Arora2

  • 1New York Genome Center, New York, NY, 10013, USA. gnarzisi@nygenome.org.

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Lancet accurately detects somatic variations, including single nucleotide variants (SNVs) and insertions/deletions (indels), in tumor and normal samples. This cancer research tool outperforms existing callers, especially for indel detection, aiding variant prioritization.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Accurate detection of somatic variations is crucial for understanding cancer.
  • Existing somatic variant callers have limitations in accuracy and sensitivity, particularly for indel detection.

Purpose of the Study:

  • To introduce Lancet, a novel somatic variant caller designed for enhanced accuracy and sensitivity.
  • To evaluate Lancet's performance against widely used somatic callers using synthetic and real sequencing data.

Main Methods:

  • Lancet jointly analyzes tumor and matched normal samples using colored de Bruijn graphs.
  • It employs a local-assembly engine to detect low-frequency mutations and longer insertions/deletions.
  • A reliable variant scoring system is integrated for effective variant prioritization.

Main Results:

  • Lancet demonstrates superior accuracy, particularly in indel detection, compared to MuTect, MuTect2, LoFreq, Strelka, and Strelka2.
  • The tool successfully detects low-frequency mutations without compromising sensitivity for longer indels.
  • Lancet offers graph-based visualization for somatic variant inspection, complementing traditional read alignment.

Conclusions:

  • Lancet provides a highly accurate and sensitive method for somatic variant detection in cancer research.
  • Its advanced features, including robust scoring and graph visualization, facilitate variant analysis and prioritization.
  • Lancet is an open-source tool available for broader research community adoption.