BioCompute Object: Difference between revisions

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{{Infobox technology standard

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| title = BioCompute Object

{{technical|date=December 2017}}

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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}}

| year_started = <!-- {{Start date|2014|07|10|df=y}} -->

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| related_standards = [[Common Workflow Language]]

| abbreviation = BCO

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| license = [[BSD licenses#3-clause license ("BSD License 2.0", "Revised BSD License", "New BSD License", or "Modified BSD License")|BSD-3-clause]]

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

}}

The '''BioCompute Object''' ('''BCO) Project''') 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]] (NGS) or [[massively parallel sequencing]] (MPS). 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> OriginallyThe started[https://www.federalregister.gov/documents/2020/07/22/2020-15771/electronic-submissions-data-standards-support-for-the-international-institute-of-electrical-and asJuly a22nd, collaborative2020 contractedition] betweenof the [[GeorgeFederal WashingtonRegister University]]announced andthat the [[Food and Drug Administration|FDA]], now supports the projectuse hasof grownBioCompute to(officially includeknown overas 20IEEE universities,2791-2020) in biotechnologyregulatory companiessubmissions, public-privateand partnershipsthe andinclusion pharmaceuticalof companiesthe includingstandard Sevenin Bridgesthe andData [[HarvardStandards MedicalCatalog School]].<ref>{{Citefor web|url=the submission of HTS data in [https://wwwweb.europeanpharmaceuticalreviewarchive.comorg/newsweb/6752420190612181016/https:/biocompute-genomic-data/|title=BioCompute Objects specifications to advance genomic data analysis|website=www.europeanpharmaceuticalreviewfda.com|language=en|accessgov/drugs/how-date=2017drugs-are-12developed-21}}<and-approved/ref>types-applications TheNDAs, BCOANDAs, aimsBLAs, toand easeINDs] theto exchange[[Center offor HTSBiologics workflowsEvaluation betweenand various organizationsResearch|CBER]], such[[Center asfor theDrug FDA,Evaluation pharmaceuticaland companiesResearch|CDER]], contractand research[[Center organizations,for bioinformaticFood platform providers,Safety and academicApplied researchersNutrition|CFSAN]].

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.

== Background ==

One of the biggest challenges in bioinformatics is documenting and sharing [[Scientific workflow system#Scientific workflows|scientific workflows]] in a such a way that the computation and its results can be peer-reviewed or reliably reproduced.<ref>{{cite journal|url=http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285|title=Ten Simple Rules for Reproducible Computational Research|first1=Geir Kjetil|last1=Sandve|first2=Anton|last2=Nekrutenko|first3=James|last3=Taylor|first4=Eivind|last4=Hovig|date=24 October 2013|publisher=|journal=PLOS Computational Biology|volume=9|issue=10|pages=e1003285|via=PLoS Journals|doi=10.1371/journal.pcbi.1003285|pmid=24204232|pmc=3812051 |bibcode=2013PLSCB...9E3285S |doi-access=free }}</ref> Bioinformatic [[Pipeline (software)|pipelines]] typically use multiple pieces of software, each of which typically has multiple versions available, multiple input parameters, multiple outputs, and possibly platform-specific configurations. As with experimental parameters in a laboratory protocol, small changes in computational parameters may have a large impact on the scientific validity of the results. The BioCompute Framework provides an [[Object-oriented design|object oriented design]] from which a BCO that contains details of a pipeline and how it was used can be constructed, [[digitally signed]], and shared. The BioCompute concept was originally developed to satisfy FDA regulatory research and review needs for evaluation, validation, and verification of genomics data. However, the Biocompute Framework follows FAIR Data Principles<ref>{{Cite journal|lastlast1=Wilkinson|firstfirst1=Mark D.|last2=Dumontier|first2=Michel|last3=Aalbersberg|first3=IJsbrand Jan|last4=Appleton|first4=Gabrielle|last5=Axton|first5=Myles|last6=Baak|first6=Arie|last7=Blomberg|first7=Niklas|last8=Boiten|first8=Jan-Willem|last9=Santos|first9=Luiz Bonino da Silva|date=2016-03-15|title=The FAIR Guiding Principles for scientific data management and stewardship|url=https://www.nature.com/articles/sdata201618|journal=Scientific Data|language=En|volume=3|pages=160018|doi=10.1038/sdata.2016.18|pmid=26978244|pmc=4792175|bibcode=2016NatSD...360018W }}</ref> and can be used broadly to provide communication and [[interoperability]] between different platforms, industries, scientists and regulators<ref>{{cite journal|url=https://www.biorxiv.org/content/early/2017/09/21/191783|title=Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results|first1=Gil|last1=Alterovitz|first2=Dennis A.|last2=Dean|first3=Carole|last3=Goble|first4=Michael R.|last4=Crusoe|first5=Stian|last5=Soiland-Reyes|first6=Amanda|last6=Bell|first7=Anais|last7=Hayes|first8=Charles Hadley H.|last8=King|first9=Elaine|last9=Johanson|first10=Elaine E.|last10=Thompson|first11=Eric|last11=Donaldson|first12=Hsinyi S.|last12=Tsang|first13=Jeremy|last13=Goecks|first14=Jonas S.|last14=Almeida|first15=Lydia|last15=Guo|first16=Mark|last16=Walderhaug|first17=Paul|last17=Walsh|first18=Robel|last18=Kahsay|first19=Toby|last19=Bloom|first20=Yuching|last20=Lai|first21=Vahan|last21=Simonyan|first22=Raja|last22=Mazumder|date=21 September 2017|publisher=|journal=bioRxiv|volume=16 |issue=12 |pages=191783|via=www.biorxiv.org|doi=10.1101/191783|pmid=30596645 |doi-access=free|pmc=6338479}}</ref>

== Utility ==

As a standardization for genomic data, BioCompute Objects are mostly useful to three groups of users: 1) academic researchers carrying out new genetic experiments, 2) pharma/biotech companies that wish to submit work to the FDA for regulatory review, and 3) clinical settings (hospitals and labs) that offer genetic tests and [[Personalized_medicine|personalized medicine]]. The utility to academic researchers is the ability to reproduce experimental data more accurately and with less uncertainty. The utility to entities wishing to submit work to the FDA is a streamlined approach, again with less uncertainty and with the ability to more accurately reproduce work. For clinical settings, it is critical that HTS data and clinical metadata be transmitted in an accurate way, ideally in a standardized way that is readable by any stakeholder, including regulatory partners.

== 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|last=|first=|date=|website=HL7 FHIR Release 3 (STU)|archive-url=|archive-date=|dead-url=|access-date=}}</ref> orMultiple [[Commonjoint Workflowimplementations Language]]are asalso under development that leverage BCO's report-centric format, including CWL (one of which is part of an active government funded public contract with a [[Researchcofounder of CWL to pilot and generate documentation for a joint BCO-CWL, as well as examples) and Object]]RO.<ref>{{Citation|last=Soiland-Reyes|first=Stian|title=hive-cwl-examples: ExamplePackaging BioCompute asObjects Researchusing Object with CWLRO-Crate|date=20162020-1209-1901|url=https://biocompute-objects.github.comio/stain/hivebco-cwlro-examples|accessdate=2017-12-21crate/}}</ref>

== BCO Consortium ==

The BioCompute Object working group facilitatesfacilitated 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. ThereThe hasgrowth beenand a continual growthwork of the BCO working group, as a direct result of the interaction between a variety of stakeholders from all interested communities, culminated in standardizationthe ofofficial computationalstandard, HTS[https://standards.ieee.org/ieee/2791/7337/ IEEE 2791-2020], which was approved in dataJanuary processing2020. 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 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]

*{{official website|https://osf.io/h59uh/}}

*[https://opensource.ieee.org/2791-object/ieee-2791-schema/ IEEE 2791-2020 open source project]

*[https://osf.io/zm97b/ Public version of the BioCompute Object (BCO) specification document Standard Trial Use (STU) Release 1.0]

[[Category:Bioinformatics software]]