Practical Guide to Multiomics Big Data Sources

Ce dossier présente un ensemble de guides pratiques concernant l'intelligence artificielle et les sources de données massives dans la recherche en chirurgie

Résumé en anglais

Over the past 2 decades, substantial advances in genotyping, next-generation sequencing, and protein capture have allowed a holistic examination of the genome, transcriptome, and proteome, respectively. Use of these data, termed -omics (or multiomics when integrated), has enhanced our understanding of the genetic basis for complex diseases. In tandem with a reduction in cost, the widespread use of electronic health record–based-phenotyping has enabled construction of the ”phenome.” Large-scale or big data analyses leverage all of these resources to develop the molecular understanding of diseases relevant to surgeons. This may allow for earlier disease detection, improvements in treatment, and potential prevention of disease progression. In this review, we provide an overview of the multiomics data in large-scale biobanks. We examine the biobank-scale data repositories that provide some of these data and discuss major limitations of these biobanks and data management, along with analytic and health equity considerations (Box).