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RUCova

This is the development version of RUCova; to use it, please install the devel version of Bioconductor.

Removes unwanted covariance from mass cytometry data


Bioconductor version: Development (3.21)

Mass cytometry enables the simultaneous measurement of dozens of protein markers at the single-cell level, producing high dimensional datasets that provide deep insights into cellular heterogeneity and function. However, these datasets often contain unwanted covariance introduced by technical variations, such as differences in cell size, staining efficiency, and instrument-specific artifacts, which can obscure biological signals and complicate downstream analysis. This package addresses this challenge by implementing a robust framework of linear models designed to identify and remove these sources of unwanted covariance. By systematically modeling and correcting for technical noise, the package enhances the quality and interpretability of mass cytometry data, enabling researchers to focus on biologically relevant signals.

Author: Rosario Astaburuaga-García [aut, cre] ORCID iD ORCID: 0000-0003-1179-4080

Maintainer: Rosario Astaburuaga-García <rosario.astaburuaga at charite.de>

Citation (from within R, enter citation("RUCova")):

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("RUCova")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("RUCova")
Removing Unwanted Covariance in mass cytometry data with RUCova HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews SingleCell, Software
Version 0.99.22
In Bioconductor since BioC 3.21 (R-4.5)
License GPL-3
Depends R (>= 4.4.0)
Imports dplyr, fastDummies, ggplot2, stringr, tibble, Matrix, ComplexHeatmap, grid, circlize, SingleCellExperiment, SummarizedExperiment, tidyverse, tidyr, magrittr, S4Vectors
System Requirements GNU make
URL https://github.com/molsysbio/RUCova
Bug Reports https://github.com/molsysbio/RUCova/issues
See More
Suggests knitr, rmarkdown, BiocManager, BiocStyle, remotes, ggpubr, ggcorrplot, ggh4x, testthat (>= 3.0.0)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package RUCova_0.99.22.tar.gz
Windows Binary (x86_64) RUCova_0.99.22.zip
macOS Binary (x86_64) RUCova_0.99.22.tgz
macOS Binary (arm64) RUCova_0.99.22.tgz
Source Repository git clone https://git.bioconductor.org/packages/RUCova
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RUCova
Bioc Package Browser https://code.bioconductor.org/browse/RUCova/
Package Short Url https://bioconductor.org/packages/RUCova/
Package Downloads Report Download Stats