Package: DepecheR 1.29.0

Jakob Theorell

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

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.

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

DepecheR_1.29.0.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
DepecheR/json (API)
NEWS

# Install 'DepecheR' in R:

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

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

testData - A 14 color flow cytometry dataset for example execution and playing around
testDataDepeche - A depeche clustering of the testData set
testDataSNE - SNE of the testData set

On BioConductor:DepecheR-1.29.0(bioc 3.24)DepecheR-1.28.0(bioc 3.23)

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

software cellbasedassays transcription differentialexpression datarepresentation immunooncology transcriptomics classification clustering dimensionreduction featureextraction flowcytometry rnaseq singlecell visualization cpp

4.92 score 21 scripts 489 downloads 2 mentions 13 exports 96 dependencies

Last updated from:0dce259f63. Checks:12 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	250
linux-devel-arm64	NOTE	319
linux-devel-x86_64	NOTE	316
source / vignettes	OK	291
linux-release-arm64	NOTE	297
linux-release-x86_64	NOTE	301
macos-release-arm64	NOTE	163
macos-release-x86_64	NOTE	285
macos-oldrel-arm64	NOTE	139
macos-oldrel-x86_64	NOTE	285
windows-devel	NOTE	221
windows-release	NOTE	233
windows-oldrel	NOTE	212
wasm-release	OK	198

Exports:dColorPlot dColorVector dContours dDensityPlot depeche dResidualPlot dScale dSplsda dViolins dWilcox groupProbPlot neighSmooth nUniqueNeighDons

Dependencies:base64enc beanplot BH BiocParallel bitops bslib cachem caTools cli ClusterR codetools collapse corpcor cpp11 DEoptimR digest doSNOW dplyr ellipse evaluate farver fastmap FNN fontawesome foreach formatR fs futile.logger futile.options gdata generics ggplot2 ggrepel glue gmodels gmp gplots gridExtra gtable gtools highr htmltools htmlwidgets igraph isoband iterators jquerylib jsonlite KernSmooth knitr labeling lambda.r lattice lifecycle magrittr MASS Matrix matrixStats memoise mime mixOmics moments pillar pkgconfig plyr purrr R6 rappdirs rARPACK RColorBrewer Rcpp RcppArmadillo RcppEigen reshape2 rgl rlang rmarkdown robustbase RSpectra S7 sass scales snow stringi stringr tibble tidyr tidyselect tinytex utf8 vctrs viridis viridisLite withr xfun yaml

Example of a cytometry data analysis with DepecheR

Jakob Theorell

Rendered fromDepecheR_test.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2020-06-05
Started: 2019-01-09

Probability plot usage

Jakob Theorell

Rendered fromGroupProbPlot_usage.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2019-12-05
Started: 2019-12-05

Help page	Topics
DepecheR: Determination of essential phenotypic elements of clusters in high-dimensional entities	DepecheR-package DepecheR
Allocation of observations to pre-established cluster centers.	dAllocate
Display third variable as color on a 2D plot	dColorPlot
Create a vector of colors of the same length as the data	dColorVector
Create density contours for two-dimensional data.	dContours
Display density on 2D plot	dDensityPlot
Perform optimization and penalized K-means clustering	depeche
Showing the residuals when subtracting the values from one group from another on a SNE plot	dResidualPlot
Scaling of a vector or a dataframe.	dScale
Sparse partial least squares discriminant analysis with paired and unpaired data	dSplsda
Create violin plots for any variables of choise	dViolins
Wilcoxon rank-sum or signed rank test comparison of subject groups in a dClust result	dWilcox
Define and plot group probabilities	groupProbPlot
Euclidean neighbor smoothing	neighSmooth
How many donors are contained among the nearest neighbors?	nUniqueNeighDons
A 14 color flow cytometry dataset for example execution and playing around	testData
A depeche clustering of the testData set	testDataDepeche
SNE of the testData set	testDataSNE

Package: DepecheR 1.29.0

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

Example of a cytometry data analysis with DepecheR

Probability plot usage

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)