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DepecheR

This is thereleased version of DepecheR; for the devel version, seeDepecheR.

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

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DOI: 10.18129/B9.bioc.DepecheR


Bioconductor version: Release (3.22)

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]ORCID iD ORCID: 0000-0001-8752-3151, Axel Theorell [aut]

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

Citation (from within R, entercitation("DepecheR")):

Installation

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

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

For older versions of R, please refer to the appropriateBioconductor 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 DepecheRHTMLR Script
Using the groupProbPlot plot function for single-cell probability displayHTMLR Script
Reference ManualPDF
NEWSText
LICENSEText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsCellBasedAssays,Classification,Clustering,DataRepresentation,DifferentialExpression,DimensionReduction,FeatureExtraction,FlowCytometry,ImmunoOncology,RNASeq,SingleCell,Software,Transcription,Transcriptomics,Visualization
Version1.26.0
In Bioconductor sinceBioC 3.9 (R-3.6) (6.5 years)
LicenseMIT + fileLICENSE
DependsR (>= 4.0)
Importsggplot2 (>= 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)
System Requirements
URL
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Suggestsuwot,testthat,knitr,rmarkdown,BiocStyle
Linking ToRcpp,RcppEigen
Enhances
Depends On Me
Imports Me
Suggests MeflowSpecs
Links To Me
Build ReportBuild Report

Package Archives

FollowInstallation instructions to use this package in your R session.

Source PackageDepecheR_1.26.0.tar.gz
Windows Binary (x86_64) DepecheR_1.26.0.zip
macOS Binary (x86_64)DepecheR_1.26.0.tgz
macOS Binary (arm64)DepecheR_1.26.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/DepecheR
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/DepecheR
Bioc Package Browserhttps://code.bioconductor.org/browse/DepecheR/
Package Short Urlhttps://bioconductor.org/packages/DepecheR/
Package Downloads ReportDownload Stats

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