Clinical bioinformatics plays a key role in the implementation of clinical next-generation sequencing (NGS) testing infrastructure. Bioinformatics workflows in a clinical laboratory are complex and therefore need to be validated as part of an end-to-end NGS assay validation before clinical use. The validation cohort should be representative of the types of samples, types of variants, lower limits of detection of the assay, as well as sequence context of the panel. When validating an NGS bioinformatics pipeline, the pipeline validation lifecycle should be adhered to. Software containers and modern software automation tools can allow the building of a scalable and reliable clinical bioinformatics infrastructure and can be implemented in clinical bioinformatics operations in a phased way depending on the size and skillset of the bioinformatics team.
Clinical bioinformatics plays a key role in the implementation of clinical NGS testing infrastructure.
NGS bioinformatics pipeline needs to be validated as part of an end-to-end NGS assay validation before clinical use.
The validation cohort should be representative of the types of samples, types of variants, lower limits of detection of the assay, as well as sequence context of the panel.
Software containers and modern software automation tools can allow building of a scalable and reliable clinical bioinformatics infrastructure.
Next-generation sequencing (NGS)-based molecular tests have revolutionized the practice of medicine with the ability to personalize diagnosis, risk assessment, and treatment of patients with cancer. In the setting of cancer predisposition, especially in the pediatric age group, NGS-based testing is increasingly playing an important role in improving overall patient care. Given the vast amounts of quantitative and complex sequencing data generated by high-throughput sequencers, resource-intensive data processing pipelines are imperative to analyze the data and identify genetic alterations of clinical relevance. Bioinformatics, specifically in the context of genomics and molecular pathology, is a field of science that uses computational, mathematical, and statistical tools to collect, organize, and analyze large and complex genetic sequencing data and related biological data. A set of bioinformatics algorithms, when executed in a predefined sequence to process NGS data, is collectively referred to as a bioinformatics pipeline. Clinical molecular laboratories performing NGS-based tests may implement one or more bioinformatics pipelines that are either custom-developed by the laboratory or provided by the sequencing platform or a third-party vendor or a combination of both. A bioinformatics pipeline typically depends on the availability of several resources, including adequate storage, compute units, network connectivity, and an appropriate software execution environment. Provisioning such resources consistently and on-demand can present several challenges in a clinical laboratory environment during the implementation of an NGS-based assay. This article will discuss some important practical considerations for laboratory directors and bioinformatics personnel when developing, validating, and managing NGS bioinformatics resources for a clinical laboratory. This article is not a comprehensive guide for all aspects of bioinformatics resource development. The readers are suggested to follow the references below for additional details.