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Enhancing Clinical Applications by Evaluation of Sensitivity and Specificity in Whole Exome Sequencing

  • Youngbeen Moon
  • , Chung Hwan Hong
  • , Young Ho Kim
  • , Jong Kwang Kim
  • , Seo Hyeon Ye
  • , Eun Kyung Kang
  • , Hye Won Choi
  • , Hyeri Cho
  • , Hana Choi
  • , Dong Eun Lee
  • , Yongdoo Choi
  • , Tae Min Kim
  • , Seong Gu Heo
  • , Namshik Han
  • , Kyeong Man Hong
  • National Cancer Center Korea
  • Dana-Farber Cancer Institute
  • Broad Institute
  • Harvard University
  • University of Cambridge

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The cost-effectiveness of whole exome sequencing (WES) remains controversial due to variant call variability, necessitating sensitivity and specificity evaluation. WES was performed by three companies (AA, BB, and CC) using reference standards composed of DNA from hydatidiform mole and individual blood at various ratios. Sensitivity was assessed by the detection rate of null–homozygote (N–H) alleles at expected variant allelic fractions, while false positive (FP) errors were counted for unexpected alleles. Sensitivity was approximately 20% for in-house results from BB and CC and around 5% for AA. Dynamic Read Analysis for GENomics (DRAGEN) analyses identified 1.34 to 1.71 times more variants, detecting over 96% of in-house variants, with sensitivity for common variants increasing to 5%. In-house FP errors varied significantly among companies (up to 13.97 times), while DRAGEN minimized this variation. Despite DRAGEN showing higher FP errors for BB and CC, the increased sensitivity highlights the importance of effective bioinformatic conditions. We also assessed the potential effects of target enrichment and proposed optimal cutoff values for the read depth and variant allele fraction in WES. Optimizing bioinformatic analysis based on sensitivity and specificity from reference standards can enhance variant detection and improve the clinical utility of WES.

Original languageEnglish
Article number13250
JournalInternational Journal of Molecular Sciences
Volume25
Issue number24
DOIs
StatePublished - Dec 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • WES
  • cancer
  • false negative error
  • false positive error
  • mutation
  • quality control
  • reference standard

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