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CDI

Clustering Deviation Index (CDI)

Bioconductor version: 3.24 · Package version: 1.11.0

Single-cell RNA-sequencing (scRNA-seq) is widely used to explore cellular variation. The analysis of scRNA-seq data often starts from clustering cells into subpopulations. This initial step has a high impact on downstream analyses, and hence it is important to be accurate. However, there have not been unsupervised metric designed for scRNA-seq to evaluate clustering performance. Hence, we propose clustering deviation index (CDI), an unsupervised metric based on the modeling of scRNA-seq UMI counts to evaluate clustering of cells.

Installation

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

BiocManager::install("CDI")

Details

MaintainerJiyuan Fang <jfanglovestats@gmail.com>
AuthorJiyuan Fang [cre, aut] (ORCID: <https://orcid.org/0000-0002-5004-4138>), Jichun Xie [ctb], Cliburn Chan [ctb], Kouros Owzar [ctb], Liuyang Wang [ctb], Diyuan Qin [ctb], Qi-Jing Li [ctb]
LicenseGPL-3 + file LICENSE
URLhttps://github.com/jichunxie/CDI
Bug Reportshttps://github.com/jichunxie/CDI/issues
Downloads rank377
Source branchdevel
biocViewsCellBasedAssays, Clustering, RNASeq, Sequencing, SingleCell, Software, Visualization

Documentation

Download

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

Source packageCDI_1.11.0.tar.gz
Windows binary (x86_64)CDI_1.11.0.zip
macOS binary (arm64)CDI_1.11.0.tgz
macOS binary (x86_64)CDI_1.11.0.tgz
Dependencies

Depends: R (>= 3.6)

Imports: matrixStats, SeuratObject, Seurat, stats, BiocParallel, ggplot2, reshape2, grDevices, ggsci, SingleCellExperiment, SummarizedExperiment, methods

Suggests: knitr, rmarkdown, RUnit, BiocGenerics, magick, BiocStyle