Enabling precision medicine via standard communication of HTS provenance, analysis, and results

Abstract

A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework (https://w3id.org/biocompute/1.3.0) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the "Open-Stand.org principles for collaborative open standards development." With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.

Fig 1. Schematic of BCO as a framework for advancing regulatory science by incorporating existing standards and introducing additional concepts that include digital signature, usability domain, validation kit, and error domain.

API, application programming interface; app, application; BCO, BioCompute Object; CGI, computer graphic imaging; FHIR, Fast Healthcare Interoperability Research; GA4GH, Global Alliance for Genomics and Health; HL7, Health Level 7; OS, operating system.

Fig 2. W3C PROV data model overview, used in Fast Healthcare Interoperability Research (FHIR) and research object (RO).

Adapted from http://www.w3.org/TR/prov-primer/.

Fig 3. Generic HTS platform schematic with proposed BCO integrations and extensions.

BCO, BioCompute Object; BD2K, Big Data to Knowledge; Desc., description; EMBL-EBI, European Molecular Biology Laboratory-European Bioinformatics Institute; Env., environmental; FDA, Food and Drug Administration; FHIR, Fast Healthcare Interoperability Research; GA4GH, Global Alliance for Genomics and Health; ID, identification; IO, input/output; NCBI, National Center for Biotechnology Information; NGS, Next-Generation Sequencing; Prereq., prerequisite; PROV, provenance specification; RO, research object; URI, uniform resource identifier; W3C, World Wide Web Consortium; Xref, external reference.