DepecheR

This is the development version of DepecheR; for the stable release version, see DepecheR.

Determination of essential phenotypic elements of clusters in high-dimensional entities


Bioconductor version: Development (3.20)

The purpose of this package is to identify traits in a dataset that can separate groups. This is done on two levels. First, clustering is performed, using an implementation of sparse K-means. Secondly, the generated clusters are used to predict outcomes of groups of individuals based on their distribution of observations in the different clusters. As certain clusters with separating information will be identified, and these clusters are defined by a sparse number of variables, this method can reduce the complexity of data, to only emphasize the data that actually matters.

Author: Jakob Theorell [aut, cre] , Axel Theorell [aut]

Maintainer: Jakob Theorell <jakob.theorell at ki.se>

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

Installation

To install this package, start R (version "4.4") and enter:


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

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

BiocManager::install("DepecheR")

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("DepecheR")
Example of a cytometry data analysis with DepecheR HTML R Script
Using the groupProbPlot plot function for single-cell probability display HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews CellBasedAssays, Classification, Clustering, DataRepresentation, DifferentialExpression, DimensionReduction, FeatureExtraction, FlowCytometry, ImmunoOncology, RNASeq, SingleCell, Software, Transcription, Transcriptomics, Visualization
Version 1.21.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License MIT + file LICENSE
Depends R (>= 4.0)
Imports ggplot2 (>= 3.1.0), MASS (>= 7.3.51), Rcpp (>= 1.0.0), dplyr (>= 0.7.8), gplots (>= 3.0.1), viridis (>= 0.5.1), foreach (>= 1.4.4), doSNOW (>= 1.0.16), matrixStats (>= 0.54.0), mixOmics(>= 6.6.1), moments (>= 0.14), grDevices (>= 3.5.2), graphics (>= 3.5.2), stats (>= 3.5.2), utils (>= 3.5), methods (>= 3.5), parallel (>= 3.5.2), reshape2 (>= 1.4.3), beanplot (>= 1.2), FNN (>= 1.1.3), robustbase (>= 0.93.5), gmodels (>= 2.18.1), collapse (>= 1.9.2), ClusterR (>= 1.3.2)
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Suggests uwot, testthat, knitr, rmarkdown, BiocStyle
Linking To Rcpp, RcppEigen
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Package Archives

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

Source Package DepecheR_1.21.0.tar.gz
Windows Binary DepecheR_1.21.0.zip
macOS Binary (x86_64) DepecheR_1.21.0.tgz
macOS Binary (arm64) DepecheR_1.21.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/DepecheR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/DepecheR
Bioc Package Browser https://code.bioconductor.org/browse/DepecheR/
Package Short Url https://bioconductor.org/packages/DepecheR/
Package Downloads Report Download Stats