This is the released version of CDI; for the devel version, see CDI.
Clustering Deviation Index (CDI)
Bioconductor version: Release (3.22)
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]
ORCID: 0000-0002-5004-4138
, Jichun Xie [ctb], Cliburn Chan [ctb], Kouros Owzar [ctb], Liuyang Wang [ctb], Diyuan Qin [ctb], Qi-Jing Li [ctb]
Maintainer: Jiyuan Fang <jfanglovestats at gmail.com>
citation("CDI")):
Installation
To install this package, start R (version "4.5") 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")
Details
| biocViews | CellBasedAssays, Clustering, RNASeq, Sequencing, SingleCell, Software, Visualization |
| Version | 1.8.3 |
| In Bioconductor since | BioC 3.18 (R-4.3) (2.5 years) |
| License | GPL-3 + file LICENSE |
| Depends | R (>= 3.6) |
| Imports | matrixStats, SeuratObject, Seurat, 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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Package Archives
Follow Installation instructions to use this package in your R session.