Bioc2026 Registration Open!

scDiagnostics

Cell type annotation diagnostics

Bioconductor version: 3.23 · Package version: 1.6.1

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.

Installation

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

BiocManager::install("scDiagnostics")

Details

MaintainerAnthony Christidis <anthony-alexander_christidis@hms.harvard.edu>
AuthorAnthony Christidis [aut, cre] (ORCID: <https://orcid.org/0000-0002-4565-6279>), Andrew Ghazi [aut], Smriti Chawla [aut], Nitesh Turaga [ctb], Ludwig Geistlinger [aut], Robert Gentleman [aut]
LicenseArtistic-2.0
URLhttps://github.com/ccb-hms/scDiagnostics
Bug Reportshttps://github.com/ccb-hms/scDiagnostics/issues
Downloads rank185
Source branchRELEASE_3_23
biocViewsAnnotation, Classification, Clustering, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 4.4.0)

Imports: SingleCellExperiment, methods, isotree, FNN, igraph, ggplot2, GGally, ggridges, SummarizedExperiment, ranger, transport, cramer, rlang, bluster, scales, MASS, stringr, Matrix, grDevices

Suggests: AUCell, BiocStyle, knitr, rmarkdown, scran, scRNAseq, SingleR, celldex, scuttle, scater, dplyr, ComplexHeatmap, grid, ragg, testthat (>= 3.0.0)