Package: nethet 1.37.0

Nicolas Staedler

nethet: A bioconductor package for high-dimensional exploration of biological network heterogeneity

Package nethet is an implementation of statistical solid methodology enabling the analysis of network heterogeneity from high-dimensional data. It combines several implementations of recent statistical innovations useful for estimation and comparison of networks in a heterogeneous, high-dimensional setting. In particular, we provide code for formal two-sample testing in Gaussian graphical models (differential network and GGM-GSA; Stadler and Mukherjee, 2013, 2014) and make a novel network-based clustering algorithm available (mixed graphical lasso, Stadler and Mukherjee, 2013).

Authors:Nicolas Staedler, Frank Dondelinger

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

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

Peer review:

On BioConductor:nethet-1.37.0(bioc 3.20)nethet-1.36.0(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

29 exports 1.38 score 67 dependencies 2 mentions

Last updated 2 months agofrom:c252a0d6ad

Exports:aggpvalbwprun_mixglassodiffnet_multisplitdiffnet_singlesplitdiffregr_multisplitdiffregr_singlesplitdot_plotexport_networkgenerate_2networksgenerate_inv_covggmgsa_multisplitgsea.irizhet_cv_glassoinvcov2parcorinvcov2parcor_arraylogratiomixglassoplot_2networksscatter_plotscreen_aic.glassoscreen_bic.glassoscreen_cv.glassoscreen_cv1se.lassoscreen_cvfix.lassoscreen_cvmin.lassoscreen_cvsqrt.lassoscreen_cvtrunc.lassosim_mixsim_mix_networks

Dependencies:BiobaseBiocGenericsBiocManagerclicodacodetoolscolorspaceCompQuadFormcorpcorcpp11DBIfansifarverfdrtoolforeachGeneNetggmggplot2glassoglmnetgluegraphGSAgtablehugeICSICSNPigraphisobanditeratorslabelinglatticelifecyclelimmalongitudinalmagrittrMASSMatrixmclustmgcvminqamitoolsmulttestmunsellmvtnormnetworknlmenumDerivpillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesshapestatmodstatnet.commonsurveysurvivaltibbleutf8vctrsviridisLitewithr

nethet

Rendered fromnethet.Rnwusingknitr::knitron Jul 02 2024.

Last update: 2019-04-30
Started: 2014-11-24

Readme and manuals

Help Manual

Help pageTopics
NetHet-packageNetHet-package
Meinshausen p-value aggregationaggpval
bwprun_mixglassobwprun_mixglasso
Differential Networkdiffnet_multisplit
Differential Network for user specified data splitsdiffnet_singlesplit
Differential Regression (multi-split version).diffregr_multisplit
Computation "split-asym" p-values.diffregr_pval
Differential Regression (single-split version).diffregr_singlesplit
Create a plot showing the edges with the highest partial correlation in any cluster.dot_plot
Export networks as a CSV table.export_network
Generate sparse invcov with overlapgenerate_2networks
generate_inv_covgenerate_inv_cov
Multi-split GGMGSA (parallelized computation)ggmgsa_multisplit
Single-split GGMGSAggmgsa_singlesplit
Irizarry approach for gene-set testinggsea.iriz
Cross-validated glasso on heterogeneous dataset with groupinghet_cv_glasso
Convert inverse covariance to partial correlationinvcov2parcor
Convert inverse covariance to partial correlation for several inverse covariance matrices collected in an array.invcov2parcor_array
Log-likelihood-ratio statistics used in DiffNetlogratio
mixglassomixglasso
mixglasso_initmixglasso_init
Plot two networks (GGMs)plot_2networks
Plotting function for object of class 'diffnet'plot.diffnet
Plotting function for object of class 'diffregr'plot.diffregr
Plotting function for object of class 'ggmgmsa'plot.ggmgsa
Plot networksplot.nethetclustering
Print function for object of class 'nethetsummmary'print.nethetsummary
Create a scatterplot showing correlation between specific nodes in the network for each pre-specified group.scatter_plot
AIC-tuned glasso with additional thresholdingscreen_aic.glasso
BIC-tuned glasso with additional thresholdingscreen_bic.glasso
Cross-validated glasso with additional thresholdingscreen_cv.glasso
Cross-validated Lasso screening (lambda.1se-rule)screen_cv1se.lasso
Cross-validated Lasso screening and upper bound on number of predictors.screen_cvfix.lasso
Cross-validation lasso screening (lambda.min-rule)screen_cvmin.lasso
Cross-validated Lasso screening and sqrt-truncation.screen_cvsqrt.lasso
Cross-validated Lasso screening and additional truncation.screen_cvtrunc.lasso
Simulate from mixture model.sim_mix
sim_mix_networkssim_mix_networks
Summary function for object of class 'diffnet'summary.diffnet
Summary function for object of class 'diffregr'summary.diffregr
Summary function for object of class 'ggmgsa'summary.ggmgsa
Summary function for object of class 'nethetclustering'summary.nethetclustering