BioCompute Object: Difference between revisions

Revision as of 15:33, 28 November 2023

Revision as of 15:58, 28 November 2023

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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, and which 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. Integration into platforms is meant to improve data handling and collaboration, and graphical representations of BCOs are often more intuitive ways of browsing or reading BCOs.
* 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 happy 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.