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("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 | ||
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 |
See More
Suggests | knitr, rmarkdown, RUnit, BiocGenerics, magick, BiocStyle |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
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 |