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Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing—A Quality Assurance Strategy

Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing—A Quality... correspondence sheet that provides all relevant metrics and require- Inferences of Mutational Status for ments of the algorithm would be helpful for both Variants Detected From Tumor-Only 3 4 LOHGIC and All-FIT and be available to researchers and clinicians using the author’s pipeline. Continuous Sequencing—A Quality monitoring of the pipeline and models (here LOHGIC Assurance Strategy and All-FIT) performance and their applicability in the 5,6 real world should be implemented. For example, TO THE EDITOR: controls should be in place to prevent the risk of model I read with great interest the article by Jalloul et al . The drift (ie, when the target population evolves away from authors examined the performance of a gene- the data set used for training). An oversight mecha- independent, information-theoretic pipeline aimed at 5 nism should be in place, with humans being on top accurately categorizing the variants identified by and a QA tactical plan implemented, eg, with audits tumor-only assays as somatic or germline. being conducted on a risk-based cadence to detect First, we would like to congratulate the authors for their potential issues, and as a consequence, models and work. The study is very relevant to the field as the pipeline http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JCO: Precision Oncology Wolters Kluwer Health

Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing—A Quality Assurance Strategy

JCO: Precision Oncology , Volume 6 – Jun 16, 2022

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Publisher
Wolters Kluwer Health
Copyright
© 2022 by American Society of Clinical Oncology
eISSN
2473-4284
DOI
10.1200/po.22.00125
Publisher site
See Article on Publisher Site

Abstract

correspondence sheet that provides all relevant metrics and require- Inferences of Mutational Status for ments of the algorithm would be helpful for both Variants Detected From Tumor-Only 3 4 LOHGIC and All-FIT and be available to researchers and clinicians using the author’s pipeline. Continuous Sequencing—A Quality monitoring of the pipeline and models (here LOHGIC Assurance Strategy and All-FIT) performance and their applicability in the 5,6 real world should be implemented. For example, TO THE EDITOR: controls should be in place to prevent the risk of model I read with great interest the article by Jalloul et al . The drift (ie, when the target population evolves away from authors examined the performance of a gene- the data set used for training). An oversight mecha- independent, information-theoretic pipeline aimed at 5 nism should be in place, with humans being on top accurately categorizing the variants identified by and a QA tactical plan implemented, eg, with audits tumor-only assays as somatic or germline. being conducted on a risk-based cadence to detect First, we would like to congratulate the authors for their potential issues, and as a consequence, models and work. The study is very relevant to the field as the pipeline

Journal

JCO: Precision OncologyWolters Kluwer Health

Published: Jun 16, 2022

References