scDiagnostics

This is the released version of scDiagnostics; for the devel version, see scDiagnostics.

Cell type annotation diagnostics


Bioconductor version: Release (3.20)

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] , 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 "4.4") and enter:


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

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

Details

biocViews Annotation, Classification, Clustering, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics
Version 1.0.0
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
See More
Suggests AUCell, BiocStyle, knitr, Matrix, rmarkdown, scran, scRNAseq, SingleR, celldex, scuttle, scater, dplyr, testthat (>= 3.0.0)
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Package Archives

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

Source Package scDiagnostics_1.0.0.tar.gz
Windows Binary (x86_64) scDiagnostics_1.0.0.zip
macOS Binary (x86_64) scDiagnostics_1.0.0.tgz
macOS Binary (arm64) scDiagnostics_1.0.0.tgz
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/
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