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PeacoQC

Peak-based selection of high quality cytometry data

Bioconductor version: 3.23 · Package version: 1.22.0

This is a package that includes pre-processing and quality control functions that can remove margin events, compensate and transform the data and that will use PeacoQCSignalStability for quality control. This last function will first detect peaks in each channel of the flowframe. It will remove anomalies based on the IsolationTree function and the MAD outlier detection method. This package can be used for both flow- and mass cytometry data.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("PeacoQC")

Details

MaintainerAnnelies Emmaneel <annelies.emmaneel@hotmail.com>
AuthorAnnelies Emmaneel [aut, cre]
LicenseGPL (>=3)
URLhttp://github.com/saeyslab/PeacoQC
Bug Reportshttp://github.com/saeyslab/PeacoQC/issues
Downloads rank712
Source branchRELEASE_3_23
biocViewsFlowCytometry, PeakDetection, Preprocessing, QualityControl, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagePeacoQC_1.22.0.tar.gz
Windows binary (x86_64)PeacoQC_1.22.0.zip
macOS binary (arm64)PeacoQC_1.22.0.tgz
macOS binary (x86_64)PeacoQC_1.22.0.tgz
Dependencies

Depends: R (>= 4.0)

Imports: circlize, ComplexHeatmap, flowCore, flowWorkspace, ggplot2, grDevices, grid, gridExtra, methods, plyr, stats, utils

Suggests: knitr, rmarkdown, BiocStyle

Reverse dependencies

Imports Me (1): CytoPipeline