scDiagnostics

This is the development version of scDiagnostics; for the stable release version, see scDiagnostics.

Cell type annotation diagnostics

Bioconductor version: Development (3.21)

The scDiagnostics package provides diagnostic plots to assess the quality of cell type assignments from single cell gene expression profiles. The implemented functionality allows to assess the reliability of cell type annotations, investigate gene expression patterns, and explore relationships between different cell types in query and reference datasets allowing users to detect potential misalignments between reference and query datasets. The package also provides visualization capabilities for diagnostics purposes.

Author: Anthony Christidis [aut, cre] (ORCID: ), Andrew Ghazi [aut], Smriti Chawla [aut], Nitesh Turaga [ctb], Ludwig Geistlinger [aut], Robert Gentleman [aut]

Maintainer: Anthony Christidis <anthony-alexander_christidis at hms.harvard.edu>

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

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scDiagnostics")

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("scDiagnostics")

1. Getting Started with scDiagnostics	HTML	R Script
2. Visualization of Cell Type Annotations	HTML	R Script
3. Evaluation of Dataset and Marker Gene Alignment	HTML	R Script
4. Detection and Analysis of Annotation Anomalies	HTML	R Script
Reference Manual	PDF
NEWS	Text

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Details

biocViews	Annotation, Classification, Clustering, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics
Version	1.1.0
In Bioconductor since	BioC 3.20 (R-4.4) (< 6 months)
License	Artistic-2.0
Depends	R (>= 4.4.0)
Imports	SingleCellExperiment, methods, isotree, ggplot2, ggridges, SummarizedExperiment, ranger, transport, speedglm, cramer, rlang, bluster, patchwork
System Requirements
URL	https://github.com/ccb-hms/scDiagnostics
Bug Reports	https://github.com/ccb-hms/scDiagnostics/issues

Suggests	AUCell, BiocStyle, knitr, Matrix, rmarkdown, scran, scRNAseq, SingleR, celldex, scuttle, scater, dplyr, testthat (>= 3.0.0)
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	scDiagnostics_1.1.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository	git clone https://git.bioconductor.org/packages/scDiagnostics
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/scDiagnostics
Bioc Package Browser	https://code.bioconductor.org/browse/scDiagnostics/
Package Short Url	https://bioconductor.org/packages/scDiagnostics/
Package Downloads Report	Download Stats