Package: RUVcorr 1.45.0

Saskia Freytag

RUVcorr: Removal of unwanted variation for gene-gene correlations and related analysis

RUVcorr allows to apply global removal of unwanted variation (ridged version of RUV) to real and simulated gene expression data.

Authors:Saskia Freytag

RUVcorr_1.45.0.tar.gz
RUVcorr_1.45.0.zip(r-4.7)RUVcorr_1.45.0.zip(r-4.6)RUVcorr_1.45.0.zip(r-4.5)
RUVcorr_1.45.0.tgz(r-4.6-any)RUVcorr_1.45.0.tgz(r-4.5-any)
RUVcorr_1.45.0.tar.gz(r-4.7-any)RUVcorr_1.45.0.tar.gz(r-4.6-any)
RUVcorr_1.45.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RUVcorr/json (API)

# Install 'RUVcorr' in R:

install.packages('RUVcorr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

On BioConductor:RUVcorr-1.45.0(bioc 3.24)RUVcorr-1.44.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

geneexpression normalization

3.78 score 15 scripts 364 downloads 2 mentions 24 exports 34 dependencies

Last updated from:696792ab66. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	194
linux-devel-x86_64	WARNING	273
source / vignettes	OK	288
linux-release-x86_64	WARNING	260
macos-release-arm64	WARNING	96
macos-oldrel-arm64	WARNING	98
windows-devel	WARNING	420
windows-release	WARNING	434
windows-oldrel	WARNING	405
wasm-release	OK	167

Exports:assessQuality background calculateThreshold compareRanks correlationPlot ECDFPlot eigenvaluePlot empNegativeControls findWeights genePlot histogramPlot is.optimizeParameters is.simulateGEdata is.Threshold is.Weights optimizeParameters PCAPlot plotDesign plotThreshold prioritise RLEPlot RUVNaiveRidge simulateGEdata wcor

Dependencies:BH Biobase BiocGenerics BiocParallel bladderbatch cli codetools corrplot cpp11 formatR futile.logger futile.options generics glue GPArotation gridExtra gtable lambda.r lattice lifecycle magrittr MASS mnormt nlme plyr psych Rcpp reshape2 rlang snow snowfall stringi stringr vctrs

Simulating and cleaning gene expression data using RUVcorr in the context of inferring gene co-expression

Simulating gene expression data with a known gene correlation structure | Independence of biological signal and systematic noise | Application of global removal of unwanted variation | Investigating the dataset design and getting data into the correct format | Selecting negative control genes | Effective application of RUVNaiveRidge | Plotting options to help make parameter choices | Gene prioritisation | Finding the correlation threshold of significant co-expression | Prioritising candidate genes

Rendered fromVignette.Rmdusingknitr::rmarkdown

Last update: 2020-04-07
Started: 2020-04-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Quality assessment for cleaning procedures.	assessQuality
Randomly choose background genes.	background
Calculates the correlation threshold.	calculateThreshold
Compare ranking of known reference gene pairs.	compareRanks
Correlation plot to compare estimated correlations with true correlations.	correlationPlot
Plot empirical cumulative distribution function for correlations.	ECDFPlot
Plot eigenvalues of SVD of the negtaive controls.	eigenvaluePlot
Empirically choose negative control genes.	empNegativeControls empNegativeControls.default empNegativeControls.simulateGEdata
Finds weights of each level of a factor.	findWeights
Plot of means and inter-quantile ranges of all genes.	genePlot
Plot histogram of correlations.	histogramPlot
Checking 'optimizeParameters' class.	is.optimizeParameters
Checking 'simulateGEdata' class.	is.simulateGEdata
Checking 'Threshold' class.	is.Threshold
Checking 'Weights' class.	is.Weights
Optimize parameters of removal of unwanted variation.	optimizeParameters
Plot principle component analysis for gene expression data.	PCAPlot
Plots an object of class 'optimizeParameters'.	plot.optimizeParameters
Plot nested design structure.	plotDesign
Plots an object of class 'Threshold'.	plotThreshold
Print an object of class 'simualteGEdata'.	print.simulateGEdata
Prioritising candidate genes.	prioritise
Plots different versions of relative log expression plots	RLEPlot
Removal of unwanted variation for gene-gene correlations.	RUVcorr
Removal of unwanted variation for gene correlations.	RUVNaiveRidge RUVNaiveRidge.default RUVNaiveRidge.simulateGEdata
Simulate gene expression data.	simulateGEdata
Calculate weighted correlations.	wcor