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]
Maintainer: Rosario Astaburuaga-García <rosario.astaburuaga at charite.de>
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 | ||
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) |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
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Links To Me | |
Build Report | Build Report |
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 |