cytofQC

cytofQC labels cells in CyTOF data with their most likely data type and the probability of belonging to each label type using a semi-supervised approach.

Key Features:

• Semi-supervised cell labeling: Assigns labels for bead, doublet, debris, and dead cells with probability scores for each label type.
• Non-destructive data cleaning: Provides labels and information to aid data cleaning without removing data from the dataset.
• Doublet discrimination: Distinguishes between doublets and large cells.

Scientific Applications:

• CyTOF data quality control: Enables initial cleaning and quality assessment of mass cytometry datasets.
• Cell classification: Supports identification and flagging of non-biological events including beads, debris, and dead cells.

Methodology:

cytofQC uses a semi-supervised approach for labeling cells with their most likely data type and the probability that they belong to each label type.