Package: PLNmodels 1.2.1

Julien Chiquet

PLNmodels: Poisson Lognormal Models

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.

Authors:Julien Chiquet [aut, cre], Mahendra Mariadassou [aut], Stéphane Robin [aut], François Gindraud [aut], Julie Aubert [ctb], Bastien Batardière [ctb], Giovanni Poggiato [ctb], Cole Trapnell [ctb], Maddy Duran [ctb]

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PLNmodels.pdf |PLNmodels.html✨
PLNmodels/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/pln-team/plnmodels/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

count-datamultivariate-analysisnetwork-inferencepcapoisson-lognormal-model

9.68 score 54 stars 224 scripts 379 downloads 26 exports 62 dependencies

Last updated 2 months agofrom:0b07e702c8. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-win-x86_64NOTENov 03 2024
R-4.5-linux-x86_64NOTENov 03 2024
R-4.4-win-x86_64NOTENov 03 2024
R-4.4-mac-x86_64NOTENov 03 2024
R-4.4-mac-aarch64NOTENov 03 2024
R-4.3-win-x86_64NOTENov 03 2024
R-4.3-mac-x86_64NOTENov 03 2024
R-4.3-mac-aarch64NOTENov 03 2024

Exports:%>%coefficient_pathcompute_offsetcompute_PLN_starting_pointextract_probsgetBestModelgetModelPLNPLN_paramPLNLDAPLNLDA_paramPLNmixturePLNmixture_paramPLNnetworkPLNnetwork_paramPLNPCAPLNPCA_parampredict_condprepare_datarPLNstability_selectionstandard_errorZIPLNZIPLN_paramZIPLNnetworkZIPLNnetwork_param

Dependencies:bitbit64callrclicodetoolscolorspacecorocorrplotcpp11descdigestdplyrellipsisfansifarverfuturefuture.applygenericsggplot2glassoFastglobalsgluegridExtragtableigraphisobandjsonlitelabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmenloptrparallellypillarpkgconfigprocessxpspsclpurrrR6RColorBrewerRcppRcppArmadillorlangsafetensorsscalesstringistringrtibbletidyrtidyselecttorchutf8vctrsviridisLitewithr

Analyzing multivariate count data with the Poisson log-normal model

PLN team

Rendered fromPLN.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2023-08-23
Started: 2019-03-24

Clustering of multivariate count data with PLN-mixture

PLN team

Rendered fromPLNmixture.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2022-12-19
Started: 2020-07-01

Description of the Trichoptera data set

PLN team

Rendered fromTrichoptera.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2022-12-19
Started: 2019-03-24

Dimension reduction of multivariate count data with PLN-PCA

PLN team

Rendered fromPLNPCA.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2022-12-19
Started: 2019-03-24

Data importation in PLNmodels

PLN team

Rendered fromImport_data.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2023-11-29
Started: 2019-03-24

Sparse structure estimation for multivariate count data with PLN-network

PLN team

Rendered fromPLNnetwork.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2022-12-19
Started: 2019-03-24

Supervized classification of multivariate count table with the Poisson discriminant Analysis

PLN team

Rendered fromPLNLDA.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2022-12-19
Started: 2019-03-24

Readme and manuals

Help Manual

Help pageTopics
Barents fish data setbarents
Extract model coefficientscoef.PLNfit
Extracts model coefficients from objects returned by 'PLNLDA()'coef.PLNLDAfit
Extract model coefficientscoef.PLNmixturefit
Extract model coefficientscoef.ZIPLNfit
Extract the regularization path of a PLNnetwork fitcoefficient_path
Compute offsets from a count data using one of several normalization schemescompute_offset
Helper function for PLN initialization.compute_PLN_starting_point
Extract edge selection frequency in bootstrap subsamplesextract_probs
Extracts model fitted values from objects returned by 'PLN()' and its variantsfitted.PLNfit
Extracts model fitted values from objects returned by 'PLNmixture()' and its variantsfitted.PLNmixturefit
Extracts model fitted values from objects returned by 'ZIPLN()' and its variantsfitted.ZIPLNfit
Best model extraction from a collection of modelsgetBestModel getBestModel.Networkfamily getBestModel.PLNmixturefamily getBestModel.PLNnetworkfamily getBestModel.PLNPCAfamily getBestModel.ZIPLNnetworkfamily
Model extraction from a collection of modelsgetModel getModel.Networkfamily getModel.PLNmixturefamily getModel.PLNnetworkfamily getModel.PLNPCAfamily getModel.ZIPLNnetworkfamily
Mollusk data setmollusk
An R6 Class to virtually represent a collection of network fitsNetworkfamily
Oaks amplicon data setoaks
Poisson lognormal modelPLN
Control of a PLN fitPLN_param
An R6 Class to represent a collection of PLNfitPLNfamily
An R6 Class to represent a PLNfit in a standard, general frameworkPLNfit
An R6 Class to represent a PLNfit in a standard, general framework, with diagonal residual covariancePLNfit_diagonal PLNLDAfit_spherical
An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariancePLNfit_fixedcov
An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariancePLNfit_spherical
Poisson lognormal model towards Linear Discriminant AnalysisPLNLDA
Control of a PLNLDA fitPLNLDA_param
An R6 Class to represent a PLNfit in a LDA frameworkPLNLDAfit
An R6 Class to represent a PLNfit in a LDA framework with diagonal covariancePLNLDAfit_diagonal
Poisson lognormal mixture modelPLNmixture
Control of a PLNmixture fitPLNmixture_param
An R6 Class to represent a collection of PLNmixturefitPLNmixturefamily
An R6 Class to represent a PLNfit in a mixture frameworkPLNmixturefit
Sparse Poisson lognormal model for network inferencePLNnetwork
Control of PLNnetwork fitPLNnetwork_param
An R6 Class to represent a collection of 'PLNnetworkfit'sPLNnetworkfamily
An R6 Class to represent a PLNfit in a sparse inverse covariance frameworkPLNnetworkfit
Poisson lognormal model towards Principal Component AnalysisPLNPCA
Control of PLNPCA fitPLNPCA_param
An R6 Class to represent a collection of PLNPCAfitPLNPCAfamily
An R6 Class to represent a PLNfit in a PCA frameworkPLNPCAfit
Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (either 'PLNnetworkfamily' or 'ZIPLNnetworkfamily')plot.Networkfamily plot.PLNnetworkfamily plot.ZIPLNnetworkfamily
Display the criteria associated with a collection of PLN fits (a PLNfamily)plot.PLNfamily
LDA visualization (individual and/or variable factor map(s)) for a 'PLNPCAfit' objectplot.PLNLDAfit
Display the criteria associated with a collection of PLNmixture fits (a PLNmixturefamily)plot.PLNmixturefamily
Mixture visualization of a 'PLNmixturefit' objectplot.PLNmixturefit
Extract and plot the network (partial correlation, support or inverse covariance) from a 'PLNnetworkfit' objectplot.PLNnetworkfit
Display the criteria associated with a collection of PLNPCA fits (a PLNPCAfamily)plot.PLNPCAfamily
PCA visualization (individual and/or variable factor map(s)) for a 'PLNPCAfit' objectplot.PLNPCAfit
Extract and plot the network (partial correlation, support or inverse covariance) from a 'ZIPLNfit_sparse' objectplot.ZIPLNfit_sparse
Predict counts conditionallypredict_cond predict_cond.PLNfit
Predict counts of a new samplepredict.PLNfit
Predict group of new samplespredict.PLNLDAfit
Prediction for a 'PLNmixturefit' objectpredict.PLNmixturefit
Predict counts of a new samplepredict.ZIPLNfit
Prepare data for use in PLN modelsprepare_data
PLN RNGrPLN
Single cell RNA-seq datascRNA
Extract variance-covariance of residuals 'Sigma'sigma.PLNfit
Extract variance-covariance of residuals 'Sigma'sigma.PLNmixturefit
Extract variance-covariance of residuals 'Sigma'sigma.ZIPLNfit
Compute the stability path by stability selectionstability_selection
Component-wise standard errors of Bstandard_error standard_error.PLNfit standard_error.PLNfit_fixedcov standard_error.PLNmixturefit standard_error.PLNnetworkfit standard_error.PLNPCAfit
Trichoptera data settrichoptera
Calculate Variance-Covariance Matrix for a fitted 'PLN()' model objectvcov.PLNfit
Zero Inflated Poisson lognormal modelZIPLN
Control of a ZIPLN fitZIPLN_param
An R6 Class to represent a ZIPLNfitZIPLNfit
An R6 Class to represent a ZIPLNfit in a standard, general framework, with diagonal residual covarianceZIPLNfit_diagonal
An R6 Class to represent a ZIPLNfit in a standard, general framework, with fixed (inverse) residual covarianceZIPLNfit_fixed
An R6 Class to represent a ZIPLNfit in a standard, general framework, with sparse inverse residual covarianceZIPLNfit_sparse
An R6 Class to represent a ZIPLNfit in a standard, general framework, with spherical residual covarianceZIPLNfit_spherical
Zero Inflated Sparse Poisson lognormal model for network inferenceZIPLNnetwork
Control of ZIPLNnetwork fitZIPLNnetwork_param
An R6 Class to represent a collection of ZIPLNnetworkZIPLNnetworkfamily