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1.
Drug Discov Today ; 29(3): 103884, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38219969

ABSTRACT

The volume of nucleic acid sequence data has exploded recently, amplifying the challenge of transforming data into meaningful information. Processing data can require an increasingly complex ecosystem of customized tools, which increases difficulty in communicating analyses in an understandable way yet is of sufficient detail to enable informed decisions or repeats. This can be of particular interest to institutions and companies communicating computations in a regulatory environment. BioCompute Objects (BCOs; an instance of pipeline documentation that conforms to the IEEE 2791-2020 standard) were developed as a standardized mechanism for analysis reporting. A suite of BCOs is presented, representing interconnected elements of a computation modeled after those that might be found in a regulatory submission but are shared publicly - in this case a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines.


Subject(s)
Computational Biology , Vaccines , High-Throughput Nucleotide Sequencing , Workflow
2.
Drug Discov Today ; 27(4): 1108-1114, 2022 04.
Article in English | MEDLINE | ID: mdl-35077912

ABSTRACT

This project demonstrates the use of the IEEE 2791-2020 Standard (BioCompute Objects [BCO]) to enable the complete and concise communication of results from next generation sequencing (NGS) analysis. One arm of a clinical trial was replicated using synthetically generated data made to resemble real biological data and then two independent analyses were performed. The first simulated a pharmaceutical regulatory submission to the US Food and Drug Administration (FDA) including analysis of results and a BCO. The second simulated an FDA review that included an independent analysis of the submitted data. Of the 118 simulated patient samples generated, 117 (99.15%) were in agreement in the two analyses. This process exemplifies how a template BCO (tBCO), including a verification kit, facilitates transparency and reproducibility, thereby reinforcing confidence in the regulatory submission process.


Subject(s)
High-Throughput Nucleotide Sequencing , Humans , Pharmaceutical Preparations , Reproducibility of Results , United States , United States Food and Drug Administration
3.
Database (Oxford) ; 20212021 03 30.
Article in English | MEDLINE | ID: mdl-33784373

ABSTRACT

Developments in high-throughput sequencing (HTS) result in an exponential increase in the amount of data generated by sequencing experiments, an increase in the complexity of bioinformatics analysis reporting and an increase in the types of data generated. These increases in volume, diversity and complexity of the data generated and their analysis expose the necessity of a structured and standardized reporting template. BioCompute Objects (BCOs) provide the requisite support for communication of HTS data analysis that includes support for workflow, as well as data, curation, accessibility and reproducibility of communication. BCOs standardize how researchers report provenance and the established verification and validation protocols used in workflows while also being robust enough to convey content integration or curation in knowledge bases. BCOs that encapsulate tools, platforms, datasets and workflows are FAIR (findable, accessible, interoperable and reusable) compliant. Providing operational workflow and data information facilitates interoperability between platforms and incorporation of future dataset within an HTS analysis for use within industrial, academic and regulatory settings. Cloud-based platforms, including High-performance Integrated Virtual Environment (HIVE), Cancer Genomics Cloud (CGC) and Galaxy, support BCO generation for users. Given the 100K+ userbase between these platforms, BioCompute can be leveraged for workflow documentation. In this paper, we report the availability of platform-dependent and platform-independent BCO tools: HIVE BCO App, CGC BCO App, Galaxy BCO API Extension and BCO Portal. Community engagement was utilized to evaluate tool efficacy. We demonstrate that these tools further advance BCO creation from text editing approaches used in earlier releases of the standard. Moreover, we demonstrate that integrating BCO generation within existing analysis platforms greatly streamlines BCO creation while capturing granular workflow details. We also demonstrate that the BCO tools described in the paper provide an approach to solve the long-standing challenge of standardizing workflow descriptions that are both human and machine readable while accommodating manual and automated curation with evidence tagging. Database URL:  https://www.biocomputeobject.org/resources.


Subject(s)
Computational Biology , Genomics , High-Throughput Nucleotide Sequencing , Humans , Reproducibility of Results , Software , Workflow
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