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treeclimbR

An algorithm to find optimal signal levels in a tree

Bioconductor version: 3.24 · Package version: 1.9.0

The arrangement of hypotheses in a hierarchical structure appears in many research fields and often indicates different resolutions at which data can be viewed. This raises the question of which resolution level the signal should best be interpreted on. treeclimbR provides a flexible method to select optimal resolution levels (potentially different levels in different parts of the tree), rather than cutting the tree at an arbitrary level. treeclimbR uses a tuning parameter to generate candidate resolutions and from these selects the optimal one.

Installation

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

BiocManager::install("treeclimbR")

Details

MaintainerCharlotte Soneson <charlottesoneson@gmail.com>
AuthorRuizhu Huang [aut] (ORCID: <https://orcid.org/0000-0003-3285-1945>), Charlotte Soneson [aut, cre] (ORCID: <https://orcid.org/0000-0003-3833-2169>)
LicenseArtistic-2.0
URLhttps://github.com/csoneson/treeclimbR
Bug Reportshttps://github.com/csoneson/treeclimbR/issues
Downloads rank323
Source branchdevel
biocViewsCellBasedAssays, Software, StatisticalMethod

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagetreeclimbR_1.9.0.tar.gz
Windows binary (x86_64)treeclimbR_1.9.0.zip
macOS binary (arm64)treeclimbR_1.9.0.tgz
macOS binary (x86_64)treeclimbR_1.9.0.tgz
Dependencies

Depends: R (>= 4.4.0)

Imports: TreeSummarizedExperiment (>= 1.99.0), edgeR, methods, SummarizedExperiment, S4Vectors, dirmult, dplyr, tibble, tidyr, ape, diffcyt, ggnewscale, ggplot2 (>= 3.4.0), viridis, ggtree, stats, utils, rlang

Suggests: knitr, rmarkdown, scales, testthat (>= 3.0.0), BiocStyle, GenomeInfoDb