Package: ClustAll 1.9.0

Asier Ortega-Legarreta

ClustAll: ClustAll: Data driven strategy to robustly identify stratification of patients within complex diseases

Data driven strategy to find hidden groups of patients with complex diseases using clinical data. ClustAll facilitates the unsupervised identification of multiple robust stratifications. ClustAll, is able to overcome the most common limitations found when dealing with clinical data (missing values, correlated data, mixed data types).

Authors:Asier Ortega-Legarreta [aut, cre], Sara Palomino-Echeverria [aut]

ClustAll_1.9.0.tar.gz
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ClustAll_1.9.0.tgz(r-4.6-any)ClustAll_1.9.0.tgz(r-4.5-any)
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ClustAll_1.9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ClustAll/json (API)

# Install 'ClustAll' in R:

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

Datasets:

heart_data - Heart Disease Dataset
obj_noNA1 - Obj_noNA1: Processed wdbc dataset for testing purposed
obj_noNA1simplify - Obj_noNA1simplify: Processed wdbc dataset for testing purposed
obj_noNAno1Validation - Obj_noNAno1Validation: Processed wdbc dataset for testing purposed
wdbc - Wdbc: Diagnostic Wisconsin Breast Cancer Database.
wdbcMIDS - WdbcMIDS: Diagnostic Wisconsin Breast Cancer Database with imputed values
wdbcNA - WdbcNA: Diagnostic Wisconsin Breast Cancer Database with missing values

On BioConductor:ClustAll-1.9.0(bioc 3.24)ClustAll-1.8.0(bioc 3.23)

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

software statisticalmethod clustering dimensionreduction principalcomponent

3.30 score 1 scripts 260 downloads 19 exports 191 dependencies

Last updated from:4df6113ca0. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	237
linux-devel-x86_64	OK	509
source / vignettes	OK	427
linux-release-x86_64	OK	595
macos-release-arm64	OK	291
macos-oldrel-arm64	OK	369
windows-devel	OK	254
windows-release	OK	242
windows-oldrel	OK	252
wasm-release	OK	187

Exports:addValidationData cluster2data createClustAll dataImputed dataOriginal dataValidation extractData extractResults JACCARD_DISTANCE_F nImputation plotJACCARD plotSANKEY processed resStratification runClustAll show showData summary_clusters validateStratification

Dependencies:abind backports base64enc bigassertr bigparallelr bigstatsr BiocGenerics bit bit64 boot broom bslib cachem car carData circlize class cli clipr clue cluster clValid codetools colorspace commonmark ComplexHeatmap cowplot cpp11 crayon crosstalk curl data.tree DEoptimR Deriv digest diptest doBy doParallel doSNOW dplyr DT ellipse emmeans estimability evaluate FactoMineR farver fastmap fBasics ff flashClust flexmix flock fontawesome forcats foreach forecast Formula fpc fracdiff fs generics GetoptLong ggplot2 ggrepel ggtext glmnet GlobalOptions glue gridtext gss gtable haven highr hms htmltools htmlwidgets igraph IRanges irlba isoband iterators jomo jpeg jquerylib jsonlite kernlab knitr labeling later lattice lazyeval leaps lifecycle litedown lme4 lmtest magrittr markdown MASS Matrix MatrixModels matrixStats mclust memoise mgcv mice mime minqa mitml modeest modelr modeltools multcompView mvtnorm networkD3 nlme nloptr nnet numDeriv ordinal otel pan parallelly pbapply pbkrtest pillar pkgconfig png prabclus prettyunits progress promises ps purrr quantreg R6 rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack readr reformulas RhpcBLASctl rjson rlang rmarkdown rmio rmutil robustbase rpart RSpectra S4Vectors S7 sass scales scatterplot3d shape showtext showtextdb snow SparseM spatial stable stabledist statip stringi stringr survival sysfonts tibble tidyr tidyselect timeDate timeSeries tinytex tzdb ucminf urca utf8 vctrs viridisLite vroom withr xfun xml2 yaml zoo

ClustAll User's Guide

Introduction | ClustAll key features: | Interpreting ClustAll Stratification Output | Installation | ClustAll Application Example | Get data from example | Create the ClustAll object | Execute the ClustAll algorithm | Represent the Jaccard Distance between population-robust stratifications | Retrieve stratification representatives | Generate Sankey diagrams comparing pairs of stratifications, or a stratification with the ground truth | Retrieve the original dataset with the selected ClustAll stratification(s) | Assess the results the sensitivity and specifity of the selected ClustAll stratifications against ground truth (if available) | Session Info

Rendered fromVignette_Clustall.Rmdusingknitr::rmarkdown

Last update: 2024-09-22
Started: 2023-11-29

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Add Validation Data to ClustAllObject	addValidationData addValidationData,ClustAllObject,numericOrCharacter-method
Class Union: characterOrNA	characterOrNA-class
ClustAllObject	ClustAllObject-class
Export Stratification Results with Original Data	cluster2data cluster2data,ClustAllObject,character-method
Create ClustAllObject for Patient Stratification Analysis	createClustAll createClustAll,data.frame,numericOrNA,ANY,characterOrNA-method
Retrieve Imputed Data from ClustAllObject	dataImputed dataImputed,ClustAllObject-method
Retrieve Original Unprocessed Data from ClustAllObject	dataOriginal dataOriginal,ClustAllObject-method
Retrieve Validation Data from ClustAllObject	dataValidation dataValidation,ClustAllObject-method
extractData	extractData extractData,ClustAllObject-method
Extract Clustering Results from ClustAllObject	extractResults extractResults,ClustAllObject-method
Heart Disease Dataset	heart_data
initializeClustAllObject	initialize,ClustAllObject-method
Retrieve Jaccard Distance Matrix for Robust Stratifications	JACCARD_DISTANCE_F JACCARD_DISTANCE_F,ClustAllObject-method
Class Union: listOrNULL	listOrNULL-class
Class Union: logicalOrNA	logicalOrNA-class
Class Union: matrixOrNULL	matrixOrNULL-class
Retrieve Number of Imputations from ClustAllObject	nImputation nImputation,ClustAllObject-method
Class Union: numericOrCharacter	numericOrCharacter numericOrCharacter-class
Class Union: numericOrNA	numericOrNA-class
obj_noNA1: Processed wdbc dataset for testing purposed	obj_noNA1
obj_noNA1simplify: Processed wdbc dataset for testing purposed	obj_noNA1simplify
obj_noNAno1Validation: Processed wdbc dataset for testing purposed	obj_noNAno1Validation
Visualize Jaccard Distances Between Robust Stratifications	plotJACCARD plotJACCARD,ClustAllObject,logicalOrNA,numericOrNA-method
Visualize Stratification Comparisons with Sankey Diagram	plotSANKEY plotSANKEY,ClustAllObject,character,logicalOrNA-method
Check Processing Status of ClustAllObject	processed processed,ClustAllObject-method
Extract Representative Stratifications from ClustAllObject	resStratification resStratification,ClustAllObject,numericOrNA,logicalOrNA,numericOrNA-method
Execute ClustALL Algorithm on a ClustAllObject	runClustAll runClustAll,ClustAllObject,numericOrNA,logicalOrNA-method
Display Summary of ClustAllObject	show,ClustAllObject-method
Retrieve Processed Data from ClustAllObject	showData showData,ClustAllObject-method
Retrieve Summary of Clustering Results from ClustAllObject	summary_clusters summary_clusters,ClustAllObject-method
Validate Stratification Results Against True Labels	validateStratification validateStratification,ClustAllObject,characterOrNA-method
wdbc: Diagnostic Wisconsin Breast Cancer Database.	wdbc
wdbcMIDS: Diagnostic Wisconsin Breast Cancer Database with imputed values	wdbcMIDS
wdbcNA: Diagnostic Wisconsin Breast Cancer Database with missing values	wdbcNA