treekoR

DOI: 10.18129/B9.bioc.treekoR    

Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations

Bioconductor version: Release (3.15)

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>

Installation

To install this package, start R (version "4.2") 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")

 

HTML	R Script	vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	Clustering, DifferentialExpression, FlowCytometry, ImmunoOncology, MassSpectrometry, SingleCell, Software, StatisticalMethod, Visualization
Version	1.4.0
In Bioconductor since	BioC 3.13 (R-4.1) (1.5 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
LinkingTo
Suggests	knitr, rmarkdown, BiocStyle, CATALYST, testthat (>= 3.0.0)
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	treekoR_1.4.0.tar.gz
Windows Binary
macOS Binary (x86_64)	treekoR_1.4.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/treekoR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/treekoR
Package Short Url	https://bioconductor.org/packages/treekoR/
Package Downloads Report	Download Stats