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treekoR

Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations

Bioconductor version: Release (3.17)

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.

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

Maintainer: Adam Chan <adam.s.chan at sydney.edu.au>

Citation (from within R, enter citation("treekoR")):

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("treekoR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("treekoR")
vignette HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, DifferentialExpression, FlowCytometry, ImmunoOncology, MassSpectrometry, SingleCell, Software, StatisticalMethod, Visualization
Version 1.8.0
In Bioconductor since BioC 3.13 (R-4.1) (2 years)
License GPL-3
Depends R (>= 4.1)
Imports stats, utils, tidyr, dplyr, data.table, ggiraph, ggplot2, hopach, ape, ggtree, patchwork, SingleCellExperiment, diffcyt, edgeR, lme4, multcomp
Linking To
Suggests knitr, rmarkdown, BiocStyle, CATALYST, testthat (>= 3.0.0)
System Requirements
Enhances
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package treekoR_1.8.0.tar.gz
Windows Binary treekoR_1.8.0.zip (64-bit only)
macOS Binary (x86_64) treekoR_1.8.0.tgz
macOS Binary (arm64) treekoR_1.8.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/treekoR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/treekoR
Bioc Package Browser https://code.bioconductor.org/browse/treekoR/
Package Short Url https://bioconductor.org/packages/treekoR/
Package Downloads Report Download Stats