PeacoQC

PeacoQC performs pre-processing and quality control of flow- and mass cytometry data by detecting peaks in each channel of the flowframe and removing anomalies to select high quality cytometry data.

Key Features:

• Pre-processing: Removes margin events, compensates, and transforms cytometry data.
• Peak Detection: Detects peaks in each channel of the flowframe as part of quality control assessment.
• Anomaly Removal: Removes anomalies based on the IsolationTree function and the MAD outlier detection method.
• Multi-platform Compatibility: Supports both flow cytometry and mass cytometry data analysis.

Scientific Applications:

• Flow Cytometry Quality Control: Identifies and selects high quality flow cytometry datasets by detecting signal stability issues.
• Mass Cytometry Quality Control: Identifies and selects high quality mass cytometry datasets by detecting signal stability issues.

Methodology:

PeacoQC uses the PeacoQCSignalStability function, which first detects peaks in each channel of the flowframe, then removes anomalies based on the IsolationTree function and the MAD outlier detection method.