Package: treekoR 1.13.0

Adam Chan

treekoR: Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations

treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; quantify a cell types as a proportion relative to all cells in a sample (%total), and, as the proportion relative to a parent population (%parent); perform significance testing using the calculated proportions; and provide an interactive html visualisation to help highlight key results.

Authors:Adam Chan [aut, cre], Ellis Patrick [ctb]

treekoR_1.13.0.tar.gz
treekoR_1.13.0.zip(r-4.5)treekoR_1.13.0.zip(r-4.4)treekoR_1.13.0.zip(r-4.3)
treekoR_1.13.0.tgz(r-4.4-any)treekoR_1.13.0.tgz(r-4.3-any)
treekoR_1.13.0.tar.gz(r-4.5-noble)treekoR_1.13.0.tar.gz(r-4.4-noble)
treekoR_1.13.0.tgz(r-4.4-emscripten)treekoR_1.13.0.tgz(r-4.3-emscripten)
treekoR.pdf |treekoR.html
treekoR/json (API)
NEWS

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

Peer review:

Datasets:

On BioConductor:treekoR-1.13.0(bioc 3.20)treekoR-1.12.0(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

9 exports 0.61 score 169 dependencies

Last updated 2 months agofrom:7c56cd9ed7

Exports:colourTreegetCellGMeansgetCellPropgetClusterTreegetTreeResultshopachToPhyloplotInteractiveHeatmaprunHOPACHtestTree

Dependencies:abindALLapeaplotaskpassbackportsbase64encBHBiobaseBiocGenericsbootbroombslibcachemcarcarDatacirclizecliclueclustercodetoolscolorRampscolorspaceComplexHeatmapConsensusClusterPluscorrplotcowplotcpp11crayoncurlcytolibdata.tableDelayedArrayDerivdiffcytdigestdoBydoParalleldplyredgeRevaluatefansifarverfastmapflowCoreFlowSOMfontawesomeforeachfsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggforceggfunggiraphggnewscaleggplot2ggplotifyggpubrggrepelggsciggsignifggtreeGlobalOptionsgluegridExtragridGraphicsgtablehighrhopachhtmltoolshtmlwidgetshttrigraphIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglatticelazyevallifecyclelimmalme4locfitmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompmunsellmvtnormnlmenloptrnnetnumDerivopensslpatchworkpbkrtestpillarpkgconfigplyrpngpolyclippolynompurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2Rhdf5librjsonrlangrmarkdownRProtoBufLibrstatixRtsneS4ArraysS4VectorssandwichsassscalesshapeSingleCellExperimentSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsyssystemfontsTH.datatibbletidyrtidyselecttidytreetinytextreeiotweenrUCSC.utilsutf8uuidvctrsviridisLitewithrxfunXMLXVectoryamlyulab.utilszlibbioczoo

treekoR

Rendered fromvignette.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2021-10-26
Started: 2021-02-02

Readme and manuals

Help Manual

Help pageTopics
TitleaddFreqBars
TitleaddHeatMap
TitleaddTree
colourTreecolourTree
COVID-19 Sample dataDeBiasi_COVID_CD8_samp
findChildrenfindChildren
geometricMeangeometricMean
getCellGMeansgetCellGMeans
getCellPropgetCellProp
getClusterTree This function takes a CATALYST sce with clusters and creates a hierarchical treegetClusterTree
getParentPropgetParentProp
getTotalPropgetTotalProp
getTreeResultsgetTreeResults
hopachToPhylohopachToPhylo
TitleplotInteractiveHeatmap
plotSigScatterplotSigScatter
runEdgeRTestsrunEdgeRTests
runGLMMTestsrunGLMMTests
runHOPACHrunHOPACH
testTreetestTree