MetaCyto

MetaCyto performs automated meta-analysis of flow and mass cytometry (CyTOF) datasets to integrate heterogeneous studies and identify comparable cell subsets for cross-study comparison.

Key Features:

• Automated Meta-Analysis: Performs automated meta-analysis across heterogeneous cytometry studies despite varying marker sets and inconsistent marker values caused by different experimental designs and instrument configurations.
• Clustering and Silhouette Scanning Methodology: Combines clustering methods with silhouette scanning to identify cell subsets commonly labeled across multiple studies.
• Cross-Study Comparability: Enables direct comparison of cytometry data by identifying consistently labeled cell subsets across studies, addressing limitations of traditional auto-gating methods.

Scientific Applications:

• Meta-analysis of cytometry cohorts: Applied to ten heterogeneous cytometry studies comprising 2,926 samples to identify multiple cell populations with differing abundance between demographic groups.

Methodology:

MetaCyto integrates clustering methods with silhouette scanning to identify common cell subsets across studies and accommodate variability in marker usage and detection values.