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| abbreviation = BCO
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The '''BioCompute Object''' ('''BCO''') project is a community-driven initiative to build a framework for standardizing and sharing computations and analyses generated from [[High-throughput sequencing]] (HTS—also referred to as [[next-generation sequencing]] or [[massively parallel sequencing]]). The project has since been [https://standards.ieee.org/ieee/2791/7337/ standardized] as IEEE 2791-2020, and the project files are maintained in an [https://opensource.ieee.org/2791-object/ieee-2791-schema/ open source repository].<ref>Simonyan V, Goecks J, Mazumder R. Biocompute Objects—A Step towards Evaluation and Validation of Biomedical Scientific Computations. PDA journal of pharmaceutical science and technology. 2017;71(2):136-146. doi:10.5731/pdajpst.2016.006734.</ref> The [https://www.federalregister.gov/documents/2020/07/22/2020-15771/electronic-submissions-data-standards-support-for-the-international-institute-of-electrical-and July 22nd, 2020 edition] of the Federal Register announced that the [[Food and Drug Administration|FDA]] now supports the use of BioCompute (officially known as IEEE 2791-2020) in regulatory submissions, and the inclusion of the standard in the Data Standards Catalog for the submission of HTS data in [https://web.archive.org/web/20190612181016/https://www.fda.gov/drugs/how-drugs-are-developed-and-approved/types-applications NDAs, ANDAs, BLAs, and INDs] to [[Center for Biologics Evaluation and Research|CBER]], [[Center for Drug Evaluation and Research|CDER]], and [[Center for Food Safety and Applied Nutrition|CFSAN]].
▲The '''BioCompute Object (BCO) Project''' is a community-driven initiative to build a framework for standardizing and sharing computations and analyses generated from [[High-throughput sequencing]] (HTS), also referred to as [[next-generation sequencing]] (NGS) or [[massively parallel sequencing]] (MPS).<ref>Simonyan V, Goecks J, Mazumder R. Biocompute Objects—A Step towards Evaluation and Validation of Biomedical Scientific Computations. PDA journal of pharmaceutical science and technology. 2017;71(2):136-146. doi:10.5731/pdajpst.2016.006734.</ref> Originally started as a collaborative contract between the [[George Washington University]] and the [[Food and Drug Administration]], the project has grown to include over 20 universities, biotechnology companies, public-private partnerships and pharmaceutical companies including Seven Bridges and [[Harvard Medical School]].<ref>{{Cite web|url=https://www.europeanpharmaceuticalreview.com/news/67524/biocompute-genomic-data/|title=BioCompute Objects specifications to advance genomic data analysis|website=www.europeanpharmaceuticalreview.com|language=en|access-date=2017-12-21}}</ref> The BCO aims to ease the exchange of HTS workflows between various organizations, such as the FDA, pharmaceutical companies, contract research organizations, bioinformatic platform providers, and academic researchers.
== Background ==
One of the biggest challenges in bioinformatics is documenting and sharing [[Scientific workflow system#Scientific workflows|scientific workflows]] in
== Utility ==
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== Format ==
The BioCompute Object is in [[JSON|json]] format and, at a minimum, contains all the software versions and parameters necessary to evaluate or verify a computational pipeline. It may also contain input data as files or links, reference genomes, or executable Docker components. A BioCompute Object can be integrated with [[FHIR|HL7 FHIR]] as a Provenance Resource.<ref>{{Cite web|url=https://www.hl7.org/fhir/provenance-example-biocompute-object.html|title=Provenance-example-biocompute-object|website=HL7 FHIR Release 3 (STU)}}</ref>
== BCO Consortium ==
The BioCompute Object working group
== Implementations ==
The simple R package biocompute<ref name="biocompute-r">{{cite web|url=https://cran.r-project.org/package=biocompute|title=CRAN - Package biocompute|publisher=cran.r-project.org|accessdate=2019-11-28}}</ref> can create, validate, and export BioCompute Objects. The [https://github.com/sbg/gcs Genomics Compliance Suite] is a Shiny app that offers similar features to regular expressions found in all modern text editors. There are several internally developed [[Open-source software|open source]] software packages and web applications that implement the BioCompute specification, three of which have been deployed in a publicly accessible [[Amazon Web Services|AWS]] [[Amazon Elastic Compute Cloud|EC2]] [[Cloud computing|cloud]]. These include an instance of the [[High-performance Integrated Virtual Environment]], the [https://github.com/biocompute-objects/bco_editor BioCompute Portal]<ref name="bco_editor">{{cite web|url=https://github.com/biocompute-objects/bco_editor|title=BioCompute Portal|publisher=github.com/biocompute-objects|accessdate=2020-06-25}}</ref> (a form-based web application that can create and edit BioCompute Objects based on the IEEE-2791-2020 [[Open standard|standard]], and a BioCompute compliant instance of [https://usegalaxy.org/ Galaxy].
Some bioinformatics platforms have built-in support for Biocompute, which let a user automatically create a BCO from a workflow and edit the descriptive content.
* DNAnexus and PrecisionFDA facilitate the generation of BCOs by importing workflows, allowing users to edit descriptive content. The platform supports metadata import and export of WDL and CWL scripts, and offers the BCOnexus tool, which is a high-level, platform-free tool with a graphical user interface that lets a user merge BCOs.
* Velsera's Seven Bridges Genomics and Cancer Genomics Cloud also have support for BioCompute by enabling direct pre-population of BCO fields from workflows.
* BioCompute has also been integrated into [https://hivelab.biochemistry.gwu.edu/ HIVE] and the main Galaxy instance, both of which similarly enable users to automatically generate BCOs and edit content within these platforms.
* BioCompute has also been implemented in the Common Fund Data Elements Playbook Partnership project. This implementation lets a user save a workflow when they're satisfied with the results, which aids in traceability through the network of independently-versioned resources, allowing users to save queries and annotate them for future use, sharing, or repeatability, aligning with its role in advancing bioinformatics practices.
Integration into platforms is meant to improve data handling and collaboration and provide effective ways for users to execute a workflow, and graphical representations of BCOs are often more intuitive ways of browsing or reading BCOs.
== References ==
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== External links ==
*[http://biocomputeobject.org/ Official Website]
*[https://opensource.ieee.org/2791-object/ieee-2791-schema/ IEEE 2791-2020 open source project]
[[Category:Bioinformatics software]]
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