BioCompute Object: Difference between revisions

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| status = [https://saaem-stg.ieee.org/project/2791.htm Active IEEE Working Group]{{dead link|date=January 2025|bot=medic}}{{cbignore|bot=medic}}

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| abbreviation = BCO

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| license = [[BSD_licensesBSD licenses#3-clause_license_clause license ("BSD_License_2BSD License 2.0",_ "Revised_BSD_LicenseRevised BSD License",_ "New_BSD_LicenseNew BSD License",_or_ or "Modified_BSD_LicenseModified BSD License")|BSD-3-clause]]

| website = {{URL|https://osf.io/h59uh/}}

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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 -- alsoHTS—also referred to as [[next-generation sequencing]] or [[massively parallel sequencing]]). The project has since been [https://standards.ieee.org/standardieee/2791-2020.html/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]].

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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. Due to the sensitive nature of regulatory filings, few direct references to material can be published. However, the project is currently funded to train FDA Reviewers and administrators to read and interpret BCOs, and currently has 4 publications either submitted or nearly submitted.

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== BCO Consortium ==

The BioCompute Object working group facilitated a means for different stakeholders to provide input on current practices on the BCO. This working group was formed during preparation for the [https://hive.biochemistry.gwu.edu/htscsrs/workshop_2017 2017 HTS Computational Standards for Regulatory Sciences Workshop], and was initially made up of the workshop participants. The growth and work of the BCO working group, as a direct result of the interaction between a variety of stakeholders from all interested communities, culminated in the official standard, [https://standards.ieee.org/ieee/2791/7337/ IEEE 2791-2020], which was approved in January of 2020. TheA [[Public–private partnership|Public-Private partnerships]] was formed between universities,GWU privateand genomic data companies, software platforms, governmentCBER and regulatory institutions havehas beenbecome an easy point of entry for new individuals or institutions into the BCO project to participate in the discussion of best practices for the objects.

== 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_ServicesAmazon Web Services|AWS]] [[Amazon_Elastic_Compute_CloudAmazon Elastic Compute Cloud|EC2]] [[Cloud_computingCloud 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_standardOpen 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.

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* 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 ==