Cluster computing is utilized to distribute analysis across multiple servers to reduce processing time from hours to minutes for common run sizes.
Supports flexible pipeline and configuration of all parameters by users. Data can be reanalyzed under varying parameter combinations to optimize for each experiment.
Run data need only be uploaded once before sharing with research teams and reviewers. Data is stored securely and shareable in password protected workspaces until publication.
Along with access to the BOLD database for identification, custom reference libraries can be defined in BOLD and directly imported into mBRAVE.