plateCore
plateCore extends R/Bioconductor packages flowCore and flowViz to automate gating and quantitative analysis of plate-based high-throughput flow cytometry data using negative control–based gating.
Key Features:
- Automated negative control-based gating: Implements negative control–driven automated gating to standardize gate determination across plate-based flow cytometry assays.
- Integration with R/Bioconductor: Leverages flowCore and flowViz S4 data structures and routines within Bioconductor for data handling and interoperability.
- High-throughput plate-based flow cytometry support: Handles large datasets typical of high-throughput screening workflows, including data from BD FACS CAP systems.
- Reproducible expression quantification: Produces expression values that align closely with manual FlowJo analysis, demonstrated on PBMC samples assayed for 189 human cell surface markers.
Scientific Applications:
- High-Throughput Flow Cytometry Screening: Analysis of large-scale screening experiments and datasets from instruments such as BD FACS CAP systems.
- Comparative reproducibility assessment: Automated analysis of PBMC samples assayed for 189 human cell surface markers to compare automated outputs with manual FlowJo results.
Methodology:
Uses negative control–based automated gating and leverages flowCore/flowViz S4 data structures and routines to compute expression values comparable to manual FlowJo analysis.
Topics
Collections
Details
- License:
- Artistic-2.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 12/10/2018
Operations
Data Inputs & Outputs
Differential protein expression analysis
Inputs
Outputs
Publications
Strain E, Hahne F, Brinkman RR, Haaland P. Analysis of High-Throughput Flow Cytometry Data Using plateCore. Advances in Bioinformatics. 2009;2009:1-10. doi:10.1155/2009/356141. PMID:19956418. PMCID:PMC2777006.
DOI: 10.1155/2009/356141
Funding: - National Institute of Biomedical Imaging and Bioengineering: EB005034
- Michael Smith Foundation for Health Research: EB005034