clustOpt/DESCRIPTION at main · gladstone-institutes/clustOpt · GitHub

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Package: clustOpt
Version: 1.2
Date: 2025-02-20
Title: Optimizing Clustering Resolution for Multi-subject Single Cell Studies
Description: Optimal clustering resolution parameters determined through Random Forests, a silhouette score-based assessment of clustering validity, and subject-wise cross-validation.
Author: Natalie Gill [aut, cre], Reuben Thomas [aut], Min-Gyoung Shin [aut], Ayushi Agrawal [aut]
Maintainer: Natalie Gill <natalie.gill@gladstone.ucsf.edu>
Authors@R: c(person("Natalie", "Gill", role = c("aut", "cre"), email = "natalie.gill@gladstone.ucsf.edu"),
	person("Min-Gyoung", "Shin", role = c("aut"), email = "mingyoung.shin@gladstone.ucsf.edu"),
	person("Ayushi", "Agrawal", role = c("aut"), email = "ayushi.agrawal@gladstone.ucsf.edu"),
	person("Erwin", "Perez", role = c("aut"), email = "perezerw@usc.edu"),
	person("Reuben", "Thomas", role = c("aut"), email = "reuben.thomas@gladstone.ucsf.edu"))
Depends:
    R (>= 4.5.0)
Imports:
    cli,
    progressr,
    future.apply,
    ranger,
    cluster,
    Seurat (>= 5.3.0),
    SeuratObject,
    dplyr (>= 1.1.3),
    ggplot2 (>= 3.3.5),
    purrr (>= 0.3.4),
    tidyr,
    Matrix,
    methods,
    stats,
    rlang
License: MIT + file LICENSE
URL: https://gladstone-institutes.github.io/clustOpt, https://github.com/gladstone-institutes/clustOpt
BugReports: https://github.com/gladstone-institutes/clustOpt/issues
RoxygenNote: 7.3.3
Encoding: UTF-8
Collate:
    'metrics.R'
    'data_preparation.R'
    'sketching.R'
    'validation.R'
    'clust_opt.R'
    'visualization.R'
Suggests:
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    BPCells,
    glmGamPoi
Config/testthat/edition: 3
VignetteBuilder: knitr