Reporting and connecting cell type names and gating definitions through ontologies

Area of Science:

• Immunology
• Bioinformatics
• Computational Biology

Background:

• Human immunology research frequently employs flow cytometry to isolate and quantify cell populations based on marker patterns.
• Cell population descriptions typically include cell type (e.g., T cells) and marker expression (e.g., CD3+).
• Standardizing these descriptions is crucial for cross-study comparisons and data integration.

Purpose of the Study:

• To develop and evaluate an ontology-driven approach for standardizing cell type and gating definitions in immunology.
• To assess the feasibility of using the Protein Ontology (PRO) and Cell Ontology (CL) for parsing and comparing flow cytometry gating data.
• To identify discrepancies in cell population definitions and propose improvements for data consistency.

Main Methods:

• Utilized a large dataset of gating definitions and cell types from the ImmPort database.
• Applied terms from the Protein Ontology (PRO) for marker patterns and the Cell Ontology (CL) for cell types.
• Employed logical axioms from CL to detect inconsistencies between cell types and their associated marker definitions.

Main Results:

• Demonstrated the ability to parse gating definitions and cell types using PRO and CL.
• Identified discrepancies between investigator-submitted gating definitions and cell types.
• Generated suggestions for new ontology terms and logical axioms to improve standardization.

Conclusions:

• Advocates for adopting a standardized format for describing gating and cell type definitions to facilitate easier comparisons.
• Recommends incorporating forward- and side-scatter information into the Ontology for Biomedical Investigations (OBI) for flow cytometry gating.
• Proposes additions to the Cell Ontology (CL) based on the analysis, including new cell types and logical axioms.