BioCompute is a standardized way to communicate an analysis. BioCompute substantially improves the clarity and reproducibility of an analysis, and can be packaged with other standards, such as Common Workflow Language. An analysis that is reported in a way that conforms to the BioCompute specification is called a BioCompute Object (BCO). A BCO abstracts the properties of an analysis away from any specific platform, tool or goal. A BCO is broken down into conceptually meaninigful "Domains" for capturing relevant information about the analysis pipeline. Major features of the BioCompute project include a "Usability Domain" for free text description by the researcher, strong data provenance and user attribution, a "Validation Kit" for quickly verifying the output of an analysis, highly extensible through a user-defined "Extension Domain," and an "Embargo Domain" for sensitive analyses not to be made public yet. See the About page for more information.

The open source repository for the project can be accessed here. Several tools have been developed to read or write an analysis as a BCO. The most popular ones are below. Other resources can be found here.






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Use HIVE, the High-Performance Integrated Virtual Environment, on AWS. HIVE is a cloud-based environment optimized for the storage and analysis of extra-large data, such as biomedical data, clinical data, next-generation sequencing (NGS) data, mass spectrometry files, confocal microscopy images, post-market surveillance data, medical recall data, and many others.
Use the BCO Portal on AWS, a platform-free, form based editor. The portal walks a user through building a BCO through drop down menus and text boxes, indicating which entries are required to adhere to the BioCompute 1.4 specification. Legacy Editor site can be found here.
Use Galaxy on AWS, the open source, web-based platform for data intensive biomedical research. Assemble your pipeline in the workspace, designate the outputs in the module boxes, and record the entire pipeline as a BCO.