Package: flowMeans 1.65.0

Nima Aghaeepour

flowMeans: Non-parametric Flow Cytometry Data Gating

Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required.

Authors:Nima Aghaeepour

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flowMeans/json (API)

# Install 'flowMeans' in R:
install.packages('flowMeans', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • x - XSample

On BioConductor:flowMeans-1.65.0(bioc 3.20)flowMeans-1.64.0(bioc 3.19)

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

bioconductor-package

5 exports 3.31 score 30 dependencies 2 dependents 17 mentions

Last updated 2 months agofrom:25ed60adeb

Exports:changepointDetectionflowMeansplotshowsummary

Dependencies:BHBiobaseBiocGenericscpp11cytolibDEoptimRfeatureflowCoreFNNkernlabKernSmoothkslatticeMatrixmatrixStatsmclustmgcvmisc3dmulticoolmvtnormnlmepcaPPplot3DpracmaRcppRhdf5librobustbaseRProtoBufLibrrcovS4Vectors

flowMeans: Non-parametric Flow Cytometry Data Gating

Rendered fromflowMeans.Rnwusingutils::Sweaveon Jul 03 2024.

Last update: 2014-06-11
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
flowMeans PackageflowMeans-package
Change-Point DetectionchangepointDetection
flowMeansflowMeans
Scatterplot of Clustering Resultsplot plot,ANY,Populations plot,ANY,Populations-method plot,flowFrame,Populations plot,flowFrame,Populations-method
Show Method for Populations Classshow show,Populations show,Populations-method
Summary Method for flowMeans Objectsummary summary,Populations summary,Populations-method
xSamplex