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Performance evaluation method for read mapping tool in clinical panel sequencing.

Hojun Lee1, Ki-Wook Lee1,2, Taeseob Lee1

  • 11Samsung Genome Institute (SGI), Samsung Medical Center (SMC), Seoul, 06351 South Korea.

Genes & Genomics
|March 24, 2018
PubMed
Summary

This study evaluated bioinformatics tools for clinical panel sequencing. Bowtie2, BWA-MEM, and Kart demonstrated high accuracy in aligning sequencing data, crucial for clinical applications.

Keywords:
Alignment toolCancerSCANClinical panel sequencingNext-Generation SequencingRead mapping

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Area of Science:

  • Genomics and Bioinformatics
  • Clinical Diagnostics

Background:

  • Next-Generation Sequencing (NGS) is advancing rapidly, increasing clinical panel sequencing use.
  • Comparative performance evaluations of NGS data analysis tools for panel sequencing are lacking.

Purpose of the Study:

  • To evaluate widely used and recent bioinformatics tools for the alignment process in panel sequencing.
  • To identify optimal tools for accurate variant detection in clinical settings.

Main Methods:

  • Simulated sequencing reads were generated from a reference genome (h19) with known variant lists.
  • Performance metrics included unmapped/misaligned reads, mapping quality, and runtime.
  • Widely used tools (Bowtie2, BWA-MEM) and a recent tool (Kart) were compared.

Main Results:

  • Bowtie2 and BWA-MEM achieved high Area Under the Curve (AUC) scores (0.9984 and 0.9970).
  • Kart demonstrated superior runtime and fewer misaligned reads, with a high AUC of 0.9723.
  • All evaluated tools showed strong performance in alignment accuracy.

Conclusions:

  • Tool selection and optimization are critical for minimizing errors in panel sequencing.
  • These findings support the use of validated tools for clinical applications and liquid biopsy studies.
  • Accurate alignment is essential for reliable variant detection in clinical genomics.