Search

Clinically relevant sequencing methodologies continue to expand in number, diversity, complexity, and scale. This evolving and varied landscape requires unique implementations in all aspects of the assay, including the wet bench, bioinformatics, and reporting. Following implementation, the informatics of many of these tests continue to change over time, from software and annotation source updates, guidelines, and knowledgebase changes to changes in underlying information technology (IT) infrastructure. Key principles can be applied when implementing the informatics of a new clinical test which can greatly improve the lab's ability to deal with these updates rapidly and reliably. In this chapter, we discuss a variety of informatics issues which span all NGS applications. In particular, there is the need for implementing a reliable, repeatable, redundant, and version-controlled bioinformatics pipeline and architecture and a discussion of common methodologies to address these needs., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: The emergence and mass utilization of high-throughput (HT) technologies, including sequencing technologies (genomics) and mass spectrometry (proteomics, metabolomics, lipids), has allowed geneticists, biologists, and biostatisticians to bridge the gap between genotype and phenotype on a massive scale. These new technologies have brought rapid advances in our understanding of cell biology, evolutionary history, microbial environments, and are increasingly providing new insights and applications towards clinical care and personalized medicine. Areas covered: The very success of this industry also translates into daunting big data challenges for researchers and institutions that extend beyond the traditional academic focus of algorithms and tools. The main obstacles revolve around analysis provenance, data management of massive datasets, ease of use of software, interpretability and reproducibility of results. Expert commentary: The authors review the challenges associated with implementing bioinformatics best practices in a large-scale setting, and highlight the opportunity for establishing bioinformatics pipelines that incorporate data tracking and auditing, enabling greater consistency and reproducibility for basic research, translational or clinical settings.