CDI

Clustering Deviation Index (CDI)


Bioconductor version: Release (3.19)

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.

Author: Jiyuan Fang [cre, aut] , Jichun Xie [ctb], Cliburn Chan [ctb], Kouros Owzar [ctb], Liuyang Wang [ctb], Diyuan Qin [ctb], Qi-Jing Li [ctb], Jichun Xie [ctb]

Maintainer: Jiyuan Fang <jfanglovestats at gmail.com>

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

Installation

To install this package, start R (version "4.4") and enter:


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

BiocManager::install("CDI")

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("CDI")
Clustering Deviation Index (CDI) Tutorial HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews CellBasedAssays, Clustering, RNASeq, Sequencing, SingleCell, Software, Visualization
Version 1.2.0
In Bioconductor since BioC 3.18 (R-4.3) (1 year)
License GPL-3 + file LICENSE
Depends R (>= 3.6)
Imports matrixStats, Seurat, SeuratObject, stats, BiocParallel, ggplot2, reshape2, grDevices, ggsci, SingleCellExperiment, SummarizedExperiment, methods
System Requirements
URL https://github.com/jichunxie/CDI
Bug Reports https://github.com/jichunxie/CDI/issues
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Suggests knitr, rmarkdown, RUnit, BiocGenerics, magick, BiocStyle
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Package Archives

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

Source Package CDI_1.2.0.tar.gz
Windows Binary (x86_64) CDI_1.2.0.zip
macOS Binary (x86_64) CDI_1.2.0.tgz
macOS Binary (arm64) CDI_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CDI
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CDI
Bioc Package Browser https://code.bioconductor.org/browse/CDI/
Package Short Url https://bioconductor.org/packages/CDI/
Package Downloads Report Download Stats