Use well-characterized, standardized datasets to assess bioinformatic tool performance with high granularity. Select from our growing catalog of annotated test data, or bring your own from the literature.
Test and assess on bug-data, development data, and samples uploaded by collaborators to get an accurate look at performance on realistic data.
Curate as you go, use metadata like cancer status, or use uncharacterized data to assess trends and performance against sanity metrics like mutation rate. Collaboratively build a body of truth data over time and dynamically evaluate them at all stages of curation.
Ensure robust coverage of edge cases and hard-to-acquire sample types with simulated data. Create spike-ins, subsamples, admixtures and titrations from existing datasets, or generate fully synthetic data.