Package: NPflow 0.13.6

Boris P Hejblum

NPflow: Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data

Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications. Method is detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi:10.1214/18-AOAS1209>.

Authors:Boris P Hejblum [aut, cre], Chariff Alkhassim [aut], Francois Caron [aut]

NPflow_0.13.6.tar.gz
NPflow_0.13.6.tar.gz(r-4.7-arm64)NPflow_0.13.6.tar.gz(r-4.7-x86_64)NPflow_0.13.6.tar.gz(r-4.6-arm64)NPflow_0.13.6.tar.gz(r-4.6-x86_64)
NPflow_0.13.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NPflow/json (API)
NEWS

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

Bug tracker:https://github.com/sistm/npflow/issues

Pkgdown/docs site:https://sistm.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.88 score 1 packages 50 scripts 363 downloads 64 exports 45 dependencies

Last updated from:265782a1b8. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK241
linux-devel-x86_64OK231
source / vignettesOK283
linux-release-arm64OK238
linux-release-x86_64OK240
wasm-releaseOK189

Exports:burn.DPMMclustcluster_est_bindercluster_est_Fmeasurecluster_est_Mbinder_normcluster_est_pearcytoScatterDPMGibbsNDPMGibbsN_parallelDPMGibbsN_SeqPriorDPMGibbsSkewNDPMGibbsSkewN_parallelDPMGibbsSkewTDPMGibbsSkewT_parallelDPMGibbsSkewT_SeqPriorDPMGibbsSkewT_SeqPrior_parallelDPMpostevalClustLossFlimitedFmeasure_costCFmeasureCFmeasureC_no0invwishrndlgamma_mvMAP_sNiW_mmEMMAP_sNiW_mmEM_vagueMAP_sNiW_mmEM_weightedMLE_gammaMLE_NiW_mmEMMLE_sNiWMLE_sNiW_mmEMmmNiWpdfmmNiWpdfCmmsNiWlogpdfmmsNiWpdfCmmvnpdfCmmvsnpdfCmmvstpdfCmmvtpdfCmvnpdfmvnpdfCmvsnpdfmvstpdfmvtpdfNuMatParCplot_ConvDPMplot_DPMplot_DPMsnplot_DPMstpostProcess.DPMMclustpriormixrCRPrNiWrNNiWsample_alphasampleClassCsimilarityMatsimilarityMat_nocostCsimilarityMatCtraceEpsCupdate_SSupdate_SSsnupdate_SSstvclust2mcoclustCwishrnd

Dependencies:clicpp11crayondplyrellipsefarverfastclusterforcatsgenericsGGallyggplot2ggstatsgluegtablehmsisobandlabelinglifecyclemagrittrpatchworkpheatmappillarpkgconfigplyrprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloreshape2rlangS7scalesstringistringrtibbletidyrtidyselecttruncnormutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Bayesian Nonparametrics for Automatic Gating of Flow Cytometry dataNPflow-package NPflow
Burning MCMC iterations from a Dirichlet Process Mixture Model.burn.DPMMclust
Point estimate of the partition for the Binder loss functioncluster_est_binder
Point estimate of the partition using the F-measure as the cost function.cluster_est_Fmeasure
Point estimate of the partition using a modified Binder loss functioncluster_est_Mbinder_norm
Gets a point estimate of the partition using posterior expected adjusted Rand index (PEAR)cluster_est_pear
Scatterplot of flow cytometry datacytoScatter
Slice Sampling of the Dirichlet Process Mixture Model with a prior on alphaDPMGibbsN
Slice Sampling of the Dirichlet Process Mixture Model with a prior on alphaDPMGibbsN_parallel
Slice Sampling of Dirichlet Process Mixture of Gaussian distributionsDPMGibbsN_SeqPrior
Slice Sampling of Dirichlet Process Mixture of skew normal distributionsDPMGibbsSkewN
Parallel Implementation of Slice Sampling of Dirichlet Process Mixture of skew normal distributionsDPMGibbsSkewN_parallel
Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributionsDPMGibbsSkewT
Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributionsDPMGibbsSkewT_parallel
Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributionsDPMGibbsSkewT_SeqPrior
Slice Sampling of Dirichlet Process Mixture of skew Student's t-distributionsDPMGibbsSkewT_SeqPrior_parallel
Posterior estimation for Dirichlet process mixture of multivariate (potentially skew) distributions modelsDPMpost
ELoss of a partition point estimate compared to a gold standardevalClustLoss
Compute a limited F-measureFlimited
Multiple cost computations with the F-measure as the loss functionFmeasure_costC
C++ implementation of the F-measure computationFmeasureC
C++ implementation of the F-measure computation without the reference class 0FmeasureC_no0
Multivariate log gamma functionlgamma_mv
EM MAP for mixture of sNiWMAP_sNiW_mmEM MAP_sNiW_mmEM_vague MAP_sNiW_mmEM_weighted
MLE for Gamma distributionMLE_gamma
EM MLE for mixture of NiWMLE_NiW_mmEM
MLE for sNiW distributed observationsMLE_sNiW
EM MLE for mixture of sNiWMLE_sNiW_mmEM
multivariate Normal inverse Wishart probability density function for multiple inputsmmNiWpdf
C++ implementation of multivariate Normal inverse Wishart probability density function for multiple inputsmmNiWpdfC
Probability density function of multiple structured Normal inverse WishartmmsNiWlogpdf
C++ implementation of multivariate structured Normal inverse Wishart probability density function for multiple inputsmmsNiWpdfC
C++ implementation of multivariate Normal probability density function for multiple inputsmmvnpdfC
C++ implementation of multivariate skew Normal probability density function for multiple inputsmmvsnpdfC
C++ implementation of multivariate Normal probability density function for multiple inputsmmvstpdfC
C++ implementation of multivariate Normal probability density function for multiple inputsmmvtpdfC
C++ implementation of multivariate Normal probability density function for multiple inputsmvnlikC
multivariate-Normal probability density functionmvnpdf
C++ implementation of multivariate normal probability density function for multiple inputsmvnpdfC
C++ implementation of multivariate skew normal likelihood function for multiple inputsmvsnlikC
multivariate Skew-Normal probability density functionmvsnpdf
C++ implementation of multivariate skew t likelihood function for multiple inputsmvstlikC
multivariate skew-t probability density functionmvstpdf
multivariate Student's t-distribution probability density functionmvtpdf
C++ implementation of similarity matrix computation using pre-computed distancesNuMatParC
Convergence diagnostic plotsplot_ConvDPM
Plot of a Dirichlet process mixture of gaussian distribution partitionplot_DPM
Plot of a Dirichlet process mixture of skew normal distribution partitionplot_DPMsn
Plot of a Dirichlet process mixture of skew t-distribution partitionplot_DPMst
Post-processing Dirichlet Process Mixture Models results to get a mixture distribution of the posterior locationspostProcess.DPMMclust
Methods for a summary of a 'DPMMclust' objectplot.summaryDPMMclust print.summaryDPMMclust summaryDPMMclust
Construction of an Empirical based priorpriormix
Generating cluster data from the Chinese Restaurant ProcessrCRP
Sampler for the concentration parameter of a Dirichlet processsample_alpha
Computes the co-clustering (or similarity) matrixsimilarityMat
C++ implementationsimilarityMat_nocostC
C++ implementationsimilarityMatC
Summarizing Dirichlet Process Mixture Modelssummary.DPMMclust
C++ implementationvclust2mcoclustC