scDiagnostics
This is the development version of scDiagnostics; to use it, please install the devel version of Bioconductor.
Cell type annotation diagnostics
Bioconductor version: Development (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("scDiagnostics")):
Installation
To install this package, start R (version "4.4") 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. Visualization of QC and Annotation Scores | HTML | R Script |
| 4. Evaluation of Dataset and Marker Gene Alignment | HTML | R Script |
| 5. Statistical Measures to Assess Dataset Alignment | HTML | R Script |
| 6. Detection of Annotation Anomalies | HTML | R Script |
| 7. Calculation of Distances Between Specific Cells and Cell Populations | HTML | R Script |
| Reference Manual |
Details
| biocViews | Annotation, Classification, Clustering, GeneExpression, RNASeq, SingleCell, Software, Transcriptomics |
| Version | 0.99.10 |
| In Bioconductor since | BioC 3.20 (R-4.4) |
| License | Artistic-2.0 |
| Depends | R (>= 4.4.0) |
| Imports | SingleCellExperiment, methods, isotree, ggplot2, 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) |
| 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_0.99.10.tar.gz |
| Windows Binary | scDiagnostics_0.99.10.zip |
| macOS Binary (x86_64) | scDiagnostics_0.99.10.tgz |
| macOS Binary (arm64) | scDiagnostics_0.99.10.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/ |
| Package Downloads Report | Download Stats |