Ontologically-Aware Automated Gating
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1. The document discusses automatically assigning ontological IDs to cell populations identified in studies using FLOCKMapper. 2. It describes the system components used, including a study dataset, FLOCK for analysis, the Cell Ontology and ImmPort ontologies for IDs, and HIPC definitions converted to a computable form. 3. It explains the mapping process involves identifying an ontological class that maps to a given HIPC class definition, addressing mismatches, and codifying the mappings as views and functions.
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TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by...
Ontologically-Aware Automated Gating
- 2. FLOCKMapper: Goal Identify the issues associated with automatically assigning ontological IDs to cell populations, whether identified programmatically or manually
- 3. System Components • SDY1 “Casale” study • FLOCK1 – FLOCKLaunch, FLOCKLoad • Cell Ontology (CL) • ImmPort CL – 2011 (generated from previous BISC contract CL) – Processed into computable form; additional curation • HIPC Lyoplate cell definitions, converted to computable form – Maecker, H., McCoy, J.P. & Nussenblatt, R. Standardizing immunophenotyping for the human immunology project. Nature reviews Immunology 12, 191-200 (2012).
- 4. Automating … - FCS conversion - Running FLOCK - Loading of results into DB
- 5. Insanely High Level Systems View
- 6. Mapping Process For a given HIPC class: 1. identify CL class that is mappable using HIPC definitions, at least in principle 2. address mismatches, if possible 3. codify as views and functions
- 7. Six Cell Types Mapped So Far CL_0002419 CL_0000815 CL_0000625 CL_0000624 CL_0000236 (Authority source is HIPC Lyoplate definitions) CL_0000623
- 9. DEMO
- 11. Determining Optimal Number of Clusters
- 12. Precision of Total T Cell Count Across Panels for Same Visit
Editor's Notes
- typology of clusters