Package: glmSparseNet 1.31.0

André Veríssimo

glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

glmSparseNet is an R-package that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. protein-protein interactions), by including network-based regularizers. glmSparseNet uses the glmnet R-package, by including centrality measures of the network as penalty weights in the regularization. The current version implements regularization based on node degree, i.e. the strength and/or number of its associated edges, either by promoting hubs in the solution or orphan genes in the solution. All the glmnet distribution families are supported, namely "gaussian", "poisson", "binomial", "multinomial", "cox", and "mgaussian".

Authors:André Veríssimo [aut, cre], Susana Vinga [aut], Eunice Carrasquinha [ctb], Marta Lopes [ctb]

glmSparseNet_1.31.0.tar.gz
glmSparseNet_1.31.0.zip(r-4.7)glmSparseNet_1.31.0.zip(r-4.6)glmSparseNet_1.31.0.zip(r-4.5)
glmSparseNet_1.31.0.tgz(r-4.6-any)glmSparseNet_1.31.0.tgz(r-4.5-any)
glmSparseNet_1.31.0.tar.gz(r-4.7-any)glmSparseNet_1.31.0.tar.gz(r-4.6-any)
glmSparseNet_1.31.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
glmSparseNet/json (API)

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

Bug tracker:https://github.com/sysbiomed/glmsparsenet/issues

Datasets:
  • string.network.700.cache - Cache of protein-protein network, as it takes some time to retrieve and process this will facilitate the vignette building

On BioConductor:glmSparseNet-1.31.0(bioc 3.24)glmSparseNet-1.30.0(bioc 3.23)

softwarestatisticalmethoddimensionreductionregressionclassificationsurvivalnetworkgraphandnetwork

7.76 score 6 stars 1 packages 59 scripts 1 mentions 29 exports 171 dependencies

Last updated from:f9c60d0cc3. Checks:1 WARNING, 2 ERROR, 7 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING290
linux-devel-x86_64ERROR458
source / vignettesOK640
linux-release-x86_64ERROR368
macos-release-arm64OK446
macos-oldrel-arm64OK255
windows-develOK1147
windows-releaseOK1014
windows-oldrelOK1158
wasm-releaseOK258

Exports:balancedCvFoldsbuildLambdabuildStringNetworkcv.glmDegreecv.glmHubcv.glmOrphancv.glmSparseNetdegreeCordegreeCovensemblGeneNamesgeneNamesglmDegreeglmHubglmOrphanglmSparseNethallmarksheuristicScalehubHeuristicmy.colorsmy.symbolsmyColorsmySymbolsnetworkCorParallelnetworkCovParallelnetworkOptionsorphanHeuristicprotein2EnsemblGeneNamesseparate2GroupsCoxstringDBhomoSapiens

Dependencies:abindAnnotationDbiaskpassbackportsBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIOBiocParallelbiomaRtBiostringsbitbit64bitopsblobbootbroomcachemcarcarDatacheckmatecigarilloclicliprcodetoolscolorspacecommonmarkcorrplotcowplotcpp11crayoncurlDBIdbplyrDelayedArrayDerivdoBydplyrexactRankTestsfarverfastmapfilelockforcatsforeachforecastformatRFormulafracdifffutile.loggerfutile.optionsgenericsGenomeInfoDbGenomicAlignmentsGenomicDataCommonsGenomicFeaturesGenomicRangesggplot2ggpubrggrepelggsciggsignifggtextglmnetgluegridExtragridtextgtablehmshttrhttr2IRangesisobanditeratorsjpegjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelitedownlme4lmtestmagrittrmarkdownMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmaxstatmemoisemgcvmicrobenchmarkmimeminqamodelrMultiAssayExperimentmvtnormnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgconfigpngpolynomprettyunitsprogresspurrrquantregR6RaggedExperimentrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRCurlRdpackreadrreformulasrestfulrRhtslibrjsonrlangRsamtoolsRSQLiterstatixrtracklayerrvestS4ArraysS4VectorsS7scalesselectrSeqinfoshapesnowSparseArraySparseMstringistringrSummarizedExperimentsurvivalsurvminersysTCGAutilstibbletidyrtidyselecttimeDatetzdbUCSC.utilsurcautf8vctrsviridisLitevroomwithrxfunXMLxml2XVectoryamlzoo

Example for Survival Data -- Breast Invasive Carcinoma
Instalation | Required Packages | Load data | Fit models | Results of Cross Validation | Coefficients of selected model from Cross-Validation | Survival curves and Log rank test | Session Info
Rendered fromexample_brca_survival.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2018-07-02

Breast survival dataset using network from STRING DB
Instalation | Required Packages | Overview | Download Data from STRING | Build network matrix | Network Statistics | Graph information | Summary of degree (indegree + outdegree) | Histogram of degree (up until 99.999% quantile) | glmSparseNet | Select balanced folds for cross-validation | glmHub model | glmOrphan model | Elastic Net model (without network-penalization) | Selected genes | Session Info
Rendered fromexample_brca_protein-protein-interactions_survival.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2018-10-01

Example for Classification Data -- Breast Invasive Carcinoma
Instalation | Required Packages | Load data | Fit models | Results of Cross Validation | Coefficients of selected model from Cross-Validation | Accuracy | Session Info
Rendered fromexample_brca_logistic.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2018-07-05

Example for Survival Data -- Prostate Adenocarcinoma
Instalation | Required Packages | Load data | Fit models | Results of Cross Validation | Coefficients of selected model from Cross-Validation | Survival curves and Log rank test | Session Info
Rendered fromexample_prad_survival.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2018-07-02

Example for Survival Data -- Skin Melanoma
Instalation | Required Packages | Load data | Fit models | Results of Cross Validation | Coefficients of selected model from Cross-Validation | Survival curves and Log rank test | Session Info
Rendered fromexample_skcm_survival.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2018-07-02

Separate 2 groups in Cox regression
Instalation | Required Packages | Prepare data | Separate using age as co-variate | Kaplan-Meier survival results | Plot | Separate using age as co-variate (group cutoff is 40% - 60%) | Separate using age as co-variate (group cutoff is 60% - 40%) | Session Info
Rendered fromseparate2GroupsCox.Rmdusingknitr::rmarkdown

Last update: 2024-02-13
Started: 2021-02-10

Readme and manuals

Help Manual

Help pageTopics
Change base dir for `.runCache.baseDir
Common call to biomaRt to avoid repetitive code.biomartLoad
Build digest of function from the actual code.buildFunctionDigest
Change cache.compression for run_cache.cacheCompression
Calculate penalty based on data.calcPenalty
Calculate/load result and save if necessary.calculateResult
Calculate combined score for STRINGdb interactions.combinedScore
Create directories for cache.createDirectoryForCache
Workaround for bug with curl when fetching specific ensembl mirror.curlWorkaround
Generic function to calculate degree based on data.degreeGeneric
Default digest method.digestCache
Calculate the upper triu of the matrix.networkGenericParallel
Worker to calculate edge weight for each pair of ixI node and following.networkWorker
Run function and save cache.runCache .runCache,function-method
Saving the cache.saveRunCache
Show messages option in .runCache.showMessage
Temporary directory for runCache.tempdirCache
Write a file in run-cache directory to explain the origin.writeReadme
Create balanced folds for cross validation using stratified samplingbalanced.cv.folds balancedCvFolds
Auxiliary function to generate suitable lambda parametersbuildLambda
Build gene network from peptide idsbuildStringNetwork
Calculate cross validating GLM model with network-based regularizationcv.glmDegree cv.glmHub cv.glmOrphan cv.glmSparseNet
Calculate the degree of the correlation network based on xdatadegreeCor
Calculate the degree of the covariance network based on xdatadegreeCov
Download files to local temporary pathdownloadFileLocal
Retrieve ensembl gene names from biomaRtensemblGeneNames
Retrieve gene names from biomaRtgeneNames
Calculate GLM model with network-based regularizationglmDegree glmHub glmOrphan glmSparseNet
Retrieve hallmarks of cancer count for geneshallmarks
Heuristic function to use in high dimensionsheuristicScale
Heuristic function to penalize nodes with low degreehubHeuristic
Custom pallete of colorsmy.colors myColors
Custom pallete of symbols in plotsmy.symbols mySymbols
Calculates the correlation networknetworkCorParallel
Calculates the covariance networknetworkCovParallel
Setup network optionsnetworkOptions
Heuristic function to penalize nodes with high degreeorphanHeuristic
Retrieve ensembl gene ids from proteinsprotein2EnsemblGeneNames
Separate data in High and Low risk groups (based on Cox model)separate2GroupsCox
Cache of protein-protein network, as it takes some time to retrieve and process this will facilitate the vignette buildingstring.network.700.cache
Download protein-protein interactions from STRING DBstringDBhomoSapiens