Recommendations for the Use of in Silico Approaches for Next-Generation Sequencing Bioinformatic Pipeline Validation: A Joint Report of the Association for Molecular Pathology, Association for Pathology Informatics, and College of American Pathologists

Eric J. Duncavage, Joshua F. Coleman, Monica E. de Baca, Sabah Kadri, Annette Leon, Mark Routbort, Somak Roy, Carlos J. Suarez, Chad Vanderbilt, Justin M. Zook

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

In silico approaches for next-generation sequencing (NGS) data modeling have utility in the clinical laboratory as a tool for clinical assay validation. In silico NGS data can take a variety of forms, including pure simulated data or manipulated data files in which variants are inserted into existing data files. In silico data enable simulation of a range of variants that may be difficult to obtain from a single physical sample. Such data allow laboratories to more accurately test the performance of clinical bioinformatics pipelines without sequencing additional cases. For example, clinical laboratories may use in silico data to simulate low variant allele fraction variants to test the analytical sensitivity of variant calling software or simulate a range of insertion/deletion sizes to determine the performance of insertion/deletion calling software. In this article, the Working Group reviews the different types of in silico data with their strengths and limitations, methods to generate in silico data, and how data can be used in the clinical molecular diagnostic laboratory. Survey data indicate how in silico NGS data are currently being used. Finally, potential applications for which in silico data may become useful in the future are presented.

Original languageEnglish
Pages (from-to)3-16
Number of pages14
JournalJournal of Molecular Diagnostics
Volume25
Issue number1
DOIs
StatePublished - Jan 2023

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