Kinds of Data

LabCAS for NIST supports the following major categories of data:

  • Cell Line Provenance Data

  • Flow Cytometry Data

  • Genome Editing Data

  • Microbial Data

Each of these categories of data is supported by a different set of features and functionality in LabCAS, such as integrated viewer applications. Access to data depends on users’ roles and permissions.

Cell Line Provenance Data

Cell Line Provenance Data captures the history and characterization of laboratory-grown cell lines. Typical records include the donor or tissue source, derivation and passage history, genetic or phenotypic modifications, authentication results (e.g., STR profiles), and contamination or mycoplasma testing outcomes. These details give researchers confidence in the identity and quality of the cells being used in experiments and help ensure traceability across projects.

TBD.

Flow Cytometry Data

Flow Cytometry Data encompasses measurements of single cells or particles as they pass through laser-based detectors. LabCAS stores raw instrument outputs (such as FCS files), acquisition parameters, fluorescence compensation matrices, staining panels, gating strategies, and derived population statistics. These datasets enable detailed immunophenotyping, viability assessments, and functional analyses of complex cell mixtures.

TBD.

Genome Editing Data

Genome Editing Data documents the design, execution, and validation of targeted DNA modifications. Typical submissions include gRNA designs or donor templates, editing workflows (e.g., CRISPR-Cas9, TALEN, base editors), efficiency metrics, sequencing-based confirmation of on-target edits, and assessments of potential off-target effects. This information supports reproducibility and regulatory compliance for engineered models and therapeutics.

TBD.

Microbial Data

Microbial Data covers the characterization of bacteria, fungi, or other microorganisms. Collections often include genome assemblies, metagenomic profiles, culture conditions, antimicrobial susceptibility panels, and phenotypic assays (e.g., growth curves, metabolite production). Associated environmental or sample provenance metadata provide context for comparative studies and biosurveillance.