Package: SIMMS 1.3.2

SIMMS: Subnetwork Integration for Multi-Modal Signatures

Algorithms to create prognostic biomarkers using biological genesets or networks.

Authors:Syed Haider [aut, cre], Paul C. Boutros [aut], Michal Grzadkowski [ctb]

SIMMS_1.3.2.tar.gz
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SIMMS_1.3.2.tgz(r-4.4-any)SIMMS_1.3.2.tgz(r-4.3-any)
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SIMMS.pdf |SIMMS.html✨
SIMMS/json (API)
NEWS

# Install 'SIMMS' in R:
install.packages('SIMMS', repos = c('https://syedhaider5.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

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

23 exports 0.36 score 78 dependencies 1 mentions 20 scripts 328 downloads

Last updated 2 years agofrom:7e3d61a175. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 16 2024
R-4.5-winOKSep 16 2024
R-4.5-linuxOKSep 16 2024
R-4.4-winOKSep 16 2024
R-4.4-macOKSep 16 2024
R-4.3-winOKSep 16 2024
R-4.3-macOKSep 16 2024

Exports:calculate.meta.survivalcalculate.network.coefficientscalculate.sensitivity.statscentre.scale.datasetcreate.classifier.multivariatecreate.classifier.univariatecreate.KM.plotcreate.sensitivity.plotcreate.survivalplotscreate.survobjderive.network.featuresdichotomize.datasetdichotomize.meta.datasetfit.coxmodelfit.interaction.modelfit.survivalmodelget.adjacency.matrixget.chisq.statsget.program.defaultsload.cancer.datasetsmake.matrixpred.survivalmodelprepare.training.validation.datasets

Dependencies:base64encbitbit64bslibcachemclicliprcodetoolscolorspacecpp11crayondata.treeDiagrammeRdigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachfsgenericsglmnetgluehighrhmshtmltoolshtmlwidgetsigraphiteratorsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemimemunsellpillarpkgconfigprettyunitsprogresspurrrR6randomForestSRCrappdirsRColorBrewerRcppRcppEigenreadrrlangrmarkdownrstudioapisassscalesshapestringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml

Rendered fromUsing-SIMMS.Rmdusingknitr::rmarkdownon Sep 16 2024.

Last update: 2020-06-05
Started: 2015-01-12

Readme and manuals

Help Manual

Help pageTopics
SIMMS - Subnetwork Integration for Multi-Modal SignaturesSIMMS-package SIMMS
Fit a meta-analytic Cox proportional hazards model to a single featurecalculate.meta.survival
Calculate Cox statistics for input datasetcalculate.network.coefficients
Computes sensitivity measurescalculate.sensitivity.stats
Centre and scale a data matrixcentre.scale.dataset
Trains and tests a multivariate survival modelcreate.classifier.multivariate
Trains and tests a univariate (per subnetwork module) survival modelcreate.classifier.univariate
Plots Kaplan-meier survival curve for a given risk grouping & survival paramscreate.KM.plot
Plots sensitivity analysis for class label dichotomization at supplied survtime cutoffscreate.sensitivity.plot
Plots Kaplan-meier survival curvescreate.survivalplots
Utility function for loading meta-analysis listscreate.survobj
Derive univariate features from pathway-derived networksderive.network.features
Dichotomize a single datasetdichotomize.dataset
Dichotomize and unlist a meta-analysis listdichotomize.meta.dataset
Fit a Cox proportional hazards modelfit.coxmodel
Cox model two features separately and togetherfit.interaction.model
Trains a multivariate survival modelfit.survivalmodel
A utility function to convert tab delimited networks file into adjacency matricesget.adjacency.matrix
Applies survdiff functionget.chisq.stats
A utility function to return the inst/ directory of the installed package and other default settingsget.program.defaults
Load all cancer meta-analysis datasetsload.cancer.datasets
Utility function used by 'get.adjacency.matrix()'make.matrix
Apply a multivariate survival model to validation datasetspred.survivalmodel
Prepare training and validation datasetsprepare.training.validation.datasets