MICon Contamination Detection Workflow for Next-Generation Sequencing Laboratories Using Microhaplotype Loci and Supervised Learning.

Autor:	Balan J; Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota. Electronic address: balan.jagadheshwar@mayo.edu., Koganti T; Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota., Basu S; Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota., Dina MA; Molecular Hematopathology Laboratory and Hematopathology Division, Mayo Clinic, Rochester, Minnesota., Artymiuk CJ; Molecular Hematopathology Laboratory and Hematopathology Division, Mayo Clinic, Rochester, Minnesota., Barr Fritcher EG; Molecular Technologies Laboratory and Anatomic Pathology Division, Mayo Clinic, Rochester, Minnesota., Halverson KE; Biospecimen Accessioning and Processing Laboratory, Mayo Clinic, Rochester, Minnesota., Wu X; Clinical Genomics Sequencing Laboratory, Mayo Clinic, Rochester, Minnesota., Jenkinson G; Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota., Viswanatha DS; Molecular Hematopathology Laboratory and Hematopathology Division, Mayo Clinic, Rochester, Minnesota. Electronic address: viswanatha.david@mayo.edu.
Jazyk:	angličtina
Zdroj:	The Journal of molecular diagnostics : JMD [J Mol Diagn] 2023 Aug; Vol. 25 (8), pp. 602-610. Date of Electronic Publication: 2023 May 25.
DOI:	10.1016/j.jmoldx.2023.05.001
Abstrakt:	Innovation in sequencing instrumentation is increasing the per-batch data volumes and decreasing the per-base costs. Multiplexed chemistry protocols after the addition of index tags have further contributed to efficient and cost-effective sequencer utilization. With these pooled processing strategies, however, comes an increased risk of sample contamination. Sample contamination poses a risk of missing critical variants in a patient sample or wrongly reporting variants derived from the contaminant, which are particularly relevant issues in oncology specimen testing in which low variant allele frequencies have clinical relevance. Small custom-targeted next-generation sequencing (NGS) panels yield limited variants and pose challenges in delineating true somatic variants versus contamination calls. A number of popular contamination identification tools have the ability to perform well in whole-genome/exome sequencing data; however, in smaller gene panels, there are fewer variant candidates for the tools to perform accurately. To prevent clinical reporting of potentially contaminated samples in small next-generation sequencing panels, we have developed MICon (Microhaplotype Contamination detection), a novel contamination detection model that uses microhaplotype site variant allele frequencies. In a heterogeneous hold-out test cohort of 210 samples, the model displayed state-of-the-art performance with an area under the receiver-operating characteristic curve of 0.995. (Copyright © 2023 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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