cytoMEM

cytoMEM automatically generates and displays quantitative labels for cell populations identified from single-cell data, conveying measured features and their levels of relative enrichment on each population.

Key Features:

• Marker Enrichment Modeling: Generates quantitative labels for pre-clustered or pre-gated cell populations with cells in rows and features in columns.
• Cross-platform Comparison: Compares MEM labels between flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry using RMSD.

Scientific Applications:

• Single-cell Population Labeling: Produces quantitative labels that convey relative enrichment levels of measured features on identified cell populations.
• Multi-omics Integration: Enables comparison of enrichment labels across diverse single-cell data types including flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry.

Methodology:

MEM accepts pre-clustered or pre-gated single-cell datasets with cells in rows and features in columns, then calculates and displays quantitative labels of relative feature enrichment for each population.