CATALYST leverages existing R/Bioconductor infrastructure by building around Biocondcutor's SingleCellExperiment class, and by providing an interface for conversion to other data structures established in the cytometry community (e.g., flowCore's flowFrame/Set classes), thus facilitating communication with existing tools for visualization (e.g., ggcyto) and gating (e.g., openCyto). The package currently provides:
- an extensive suit of visualizations for differential discovery
- a pipeline for preprocessing of cytometry data, including
- normalization using bead standards
- single-cell deconvolution
- bead-based compensation
- Chevrier S☆, Crowell HL☆, Zanotelli VRT☆, Engler S, Robinson MD & Bodenmiller B (2018):
Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry. Cell Systems 6(5):612-620.e5. - Nowicka M, Krieg C, Crowell HL, Weber LM, Hartmann FJ, Guglietta S, Becher B, Levesque MP & Robinson MD (2017):
CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets. F1000Resaearch 6:748.
CATALYST is still under active development. We greatly welcome (and highly encourage!) all feedback, bug reports and suggestions for improvement HERE. Please make sure to raise issues with a reproducible example and the output of your sessionInfo().