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
| Maintainer | Anthony Christidis <anthony-alexander_christidis@hms.harvard.edu> |
| Author | Anthony 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] |
| License | Artistic-2.0 |
| URL | https://github.com/ccb-hms/scDiagnostics |
| Bug Reports | https://github.com/ccb-hms/scDiagnostics/issues |
| Downloads rank | 185 |
| Source branch | RELEASE_3_23 |
| biocViews | Annotation, Classification, Clustering, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics |
Documentation
- Getting Started with scDiagnostics
- Visualization of Cell Type Annotations
- Evaluation of Dataset and Marker Gene Alignment
- Detection and Analysis of Annotation Anomalies
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)