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Germline Testing Data Validate Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing.

Nahed JalloulIsrael GomySamantha StokesAlexander GusevBruce E JohnsonNeal I LindemanLaura MacconaillShridar GanesanJudy E GarberHossein Khiabanian
Published in: JCO precision oncology (2021)
Analyzing tumor-only data in the context of specimens' tumor cell content allows precise, systematic exclusion of somatic variants and suggests a balance between type 1 and 2 errors for identification of patients with candidate PGV for standard germline testing. Although technical or systematic errors in measuring variant allele frequency could result in incorrect inference, misestimation of specimen purity could result in inferring somatic variants as germline in somatically mutated tumor suppressor genes. A user-friendly bioinformatics application facilitates objective analysis of tumor-only data in clinical settings.
Keyphrases
  • copy number
  • single cell
  • electronic health record
  • big data
  • patient safety
  • gene expression
  • dna damage
  • bone marrow
  • bioinformatics analysis
  • oxidative stress
  • deep learning
  • artificial intelligence