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
SIMMS_1.3.2.zip(r-4.7-any)SIMMS_1.3.2.zip(r-4.6-any)SIMMS_1.3.2.zip(r-4.5-any)
SIMMS_1.3.2.tgz(r-4.6-any)SIMMS_1.3.2.tgz(r-4.5-any)
SIMMS_1.3.2.tar.gz(r-4.7-any)SIMMS_1.3.2.tar.gz(r-4.6-any)
SIMMS_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SIMMS/json (API)

# Install 'SIMMS' in R:

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

On CRAN:

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

2.30 score 20 scripts 304 downloads 1 mentions 23 exports 75 dependencies

Last updated from:7e3d61a175. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	148
source / vignettes	OK	167
linux-release	OK	152
macos-release	OK	132
macos-oldrel	OK	121
windows-devel	OK	120
windows-release	OK	100
windows-oldrel	OK	118
wasm-release	OK	132

Exports:calculate.meta.survival calculate.network.coefficients calculate.sensitivity.stats centre.scale.dataset create.classifier.multivariate create.classifier.univariate create.KM.plot create.sensitivity.plot create.survivalplots create.survobj derive.network.features dichotomize.dataset dichotomize.meta.dataset fit.coxmodel fit.interaction.model fit.survivalmodel get.adjacency.matrix get.chisq.stats get.program.defaults load.cancer.datasets make.matrix pred.survivalmodel prepare.training.validation.datasets

Dependencies:base64enc bit bit64 bslib cachem cli clipr codetools cpp11 crayon data.tree DiagrammeR digest doParallel dplyr evaluate farver fastmap fontawesome foreach fs generics glmnet glue highr hms htmltools htmlwidgets igraph iterators jquerylib jsonlite knitr labeling lattice lifecycle magrittr MASS Matrix memoise mime pillar pkgconfig prettyunits progress purrr R6 randomForestSRC rappdirs RColorBrewer Rcpp RcppEigen readr rlang rmarkdown rstudioapi sass scales shape stringi stringr survival tibble tidyr tidyselect tinytex tzdb utf8 vctrs viridisLite visNetwork vroom withr xfun yaml

Rendered fromUsing-SIMMS.Rmdusingknitr::rmarkdown

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

Citation

Readme and manuals

Help Manual

Help page	Topics
SIMMS - Subnetwork Integration for Multi-Modal Signatures	SIMMS-package SIMMS
Fit a meta-analytic Cox proportional hazards model to a single feature	calculate.meta.survival
Calculate Cox statistics for input dataset	calculate.network.coefficients
Computes sensitivity measures	calculate.sensitivity.stats
Centre and scale a data matrix	centre.scale.dataset
Trains and tests a multivariate survival model	create.classifier.multivariate
Trains and tests a univariate (per subnetwork module) survival model	create.classifier.univariate
Plots Kaplan-meier survival curve for a given risk grouping & survival params	create.KM.plot
Plots sensitivity analysis for class label dichotomization at supplied survtime cutoffs	create.sensitivity.plot
Plots Kaplan-meier survival curves	create.survivalplots
Utility function for loading meta-analysis lists	create.survobj
Derive univariate features from pathway-derived networks	derive.network.features
Dichotomize a single dataset	dichotomize.dataset
Dichotomize and unlist a meta-analysis list	dichotomize.meta.dataset
Fit a Cox proportional hazards model	fit.coxmodel
Cox model two features separately and together	fit.interaction.model
Trains a multivariate survival model	fit.survivalmodel
A utility function to convert tab delimited networks file into adjacency matrices	get.adjacency.matrix
Applies survdiff function	get.chisq.stats
A utility function to return the inst/ directory of the installed package and other default settings	get.program.defaults
Load all cancer meta-analysis datasets	load.cancer.datasets
Utility function used by 'get.adjacency.matrix()'	make.matrix
Apply a multivariate survival model to validation datasets	pred.survivalmodel
Prepare training and validation datasets	prepare.training.validation.datasets

Package: SIMMS 1.3.2

SIMMS: Subnetwork Integration for Multi-Modal Signatures

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)