Package: ClustAll 1.1.0

Asier Ortega-Legarreta

ClustAll: ClustAll: Data driven strategy to find groups 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_1.1.0.tar.gz
ClustAll_1.1.0.zip(r-4.5)ClustAll_1.1.0.zip(r-4.4)ClustAll_1.1.0.zip(r-4.3)
ClustAll_1.1.0.tgz(r-4.4-any)ClustAll_1.1.0.tgz(r-4.3-any)
ClustAll_1.1.0.tar.gz(r-4.5-noble)ClustAll_1.1.0.tar.gz(r-4.4-noble)
ClustAll_1.1.0.tgz(r-4.4-emscripten)ClustAll_1.1.0.tgz(r-4.3-emscripten)
ClustAll.pdf |ClustAll.html✨
ClustAll/json (API)
NEWS

# Install 'ClustAll' in R:

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

Datasets:

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-1.1.0(bioc 3.20)ClustAll-1.0.0(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

17 exports 1.38 score 179 dependencies

Last updated 2 months agofrom:86f35b61ad

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

Dependencies:abind backports base64enc bigassertr bigparallelr bigstatsr BiocGenerics bit bit64 boot brio broom bslib cachem callr car carData circlize class cli clipr clue cluster clValid codetools colorspace ComplexHeatmap cowplot cpp11 crayon crosstalk DEoptimR desc diffobj digest diptest doParallel doSNOW dplyr DT ellipse emmeans estimability evaluate FactoMineR fansi farver fastmap fBasics ff flashClust flexmix flock fontawesome forcats foreach fpc fs generics GetoptLong ggplot2 ggrepel glmnet GlobalOptions glue gss gtable haven highr hms htmltools htmlwidgets httpuv igraph IRanges isoband iterators jomo jquerylib jsonlite kernlab knitr labeling later lattice lazyeval leaps lifecycle lme4 magrittr MASS Matrix MatrixModels matrixStats mclust memoise mgcv mice mime minqa mitml modeest modeltools multcompView munsell mvtnorm networkD3 nlme nloptr nnet numDeriv ordinal pan parallelly pbapply pbkrtest pillar pkgbuild pkgconfig pkgload png prabclus praise prettyunits processx progress promises ps purrr quantreg R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen readr rematch2 RhpcBLASctl rjson rlang rmarkdown rmio rmutil robustbase rpart rprojroot RSpectra S4Vectors sass scales scatterplot3d shape snow SparseM spatial stable stabledist statip stringi stringr survival testthat tibble tidyr tidyselect timeDate timeSeries tinytex tzdb ucminf utf8 vctrs viridisLite vroom waldo withr xfun yaml

ClustAll User's Guide

Asier Ortega-Legarreta and Sara Palomino-Echeverria

Rendered fromVignette_Clustall.Rmdusingknitr::rmarkdownon Jun 17 2024.

Last update: 2024-03-31
Started: 2023-11-29

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Add the validation data into the ClustAllObject	addValidationData addValidationData,ClustAllObject,numericOrCharacter-method
characterOrNA Class union of character, null or missing	characterOrNA characterOrNA-class
ClustAllObject	ClustAllObject-class
cluster2data	cluster2data cluster2data,ClustAllObject,character-method
Creates ClustAllObject and perform imputations to deal with missing values	createClustAll createClustAll,data.frame,numericOrNA,ANY,characterOrNA-method
Retrieve the imputed data from ClustAllObject	dataImputed dataImputed,ClustAllObject-method
Retrieve the initial dataOriginal from ClustAllObject	dataOriginal dataOriginal,ClustAllObject-method
Retrieve the original data labelling from ClustAllObject	dataValidation dataValidation,ClustAllObject-method
initializeClustAllObject	initialize,ClustAllObject-method
Retrieve the matrix with the Jaccard distances derived from the robust populations stratifications in ClustAllObject	JACCARD_DISTANCE_F JACCARD_DISTANCE_F,ClustAllObject-method
Class Union listOrNULL	listOrNULL listOrNULL-class
logicalOrNA	logicalOrNA logicalOrNA-class
matrixOrNULL	matrixOrNULL matrixOrNULL-class
Retrieve the number of imputations applied at the imputation step from ClustAllObject	nImputation nImputation,ClustAllObject-method
numericOrCharacter	numericOrCharacter numericOrCharacter-class
Class Union numericOrNA	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
Correlation matrix heatmap showing the Jaccard distance between robust stratifications in the ClustAllObject	plotJACCARD plotJACCARD,ClustAllObject,logicalOrNA,numericOrNA-method
Plots Sankey Diagram showing the cluster distribution and shifts between a pair of stratifications derived from ClustAllObject	plotSANKEY plotSANKEY,ClustAllObject,character,logicalOrNA-method
Retrieve logical if runClustAll has been executed considering ClustAllObject as input	processed processed,ClustAllObject-method
Show the stratification representatives from the ClustAllObject	resStratification resStratification,ClustAllObject,numericOrNA,logicalOrNA,numericOrNA-method
ClustAll: Data driven strategy to find hidden subgroups of patients within complex diseases using clinical data	runClustAll runClustAll,ClustAllObject,numericOrNA,logicalOrNA-method
show method for ClustAllObject	show,ClustAllObject-method
Retrieve the initial data from ClustAllObject	showData showData,ClustAllObject-method
Retrieve the resulting stratifications for each combination of clusterings method (distance + clustering algorithm) and depth from ClustAllObject	summary_clusters summary_clusters,ClustAllObject-method
validateStratification	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