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Material Measurement Laboratory

Biosystems and Biomaterials Division

FCSC Working Group 3

Data Repository and Centralized Data Analysis

Working Group 3 (WG3) organizes, analyzes and disseminates the data generated by Consortium interlaboratory studies (ILS). This work includes developing and applying standardized metadata schemas capturing relevant aspects of ILS design, such as organization, site, instrument, calibrant, control, sample, etc. This work also includes collaborative development of a robust data repository for cataloging input data, post-processed data, and accessory files and analysis reports. Activities in progress include:

Interlaboratory study input data curation and dissemination Ingest and structuring of thousands of .FCS files reported by ILS1 participants to facilitate downstream bulk analysis. ILS1 data available upon request to Consortium members for use in analysis pipelines includes:
- A development data sub-set of all .FCS files measured by five individual instruments from ILS1
- Complete dataset contributed by all 17 Consortium members participating in ILS1 (~ 500 Gb)
Centralized analysis of interlaboratory study data to produce high-quality reference flow cytometry datasets A sub-team of WG3 participants is pursing a consensus analysis of all WG2-ILS1 data through five key analysis stages of file QC and disposition (include/exclude), compensation/unmixing, calibration, transformation, and gating. This centralized data analysis (CDA) will generate the baseline consensus results for WG2-ILS1 TBMNK cell count and cell health and enable reproducible generation of the analyzed results from the input data. Post-processed .FCS data and associated analysis reports will comprise a high-quality reference flow cytometry dataset for healthy-donor PBMC samples.
Curation and dissemination of analyzed data and analysis parameters alongside original inputs The CDA of WG2-ILS1 is driving the need to develop rational strategies for storing post-processed, or "derived" .FCS files alongside the original, as-measured input data and for applying metadata annotations that explain the processing applied and allow the processing to be reproduced. Providing robust, contextual access to the WG2-ILS1 data before and after consensus processing is expected to enable opportunities for artificial intelligence/machine learning (AI/ML) development and training for flow cytometry assay data.