Package: scDiagnostics 1.1.0

Anthony Christidis

scDiagnostics: Cell type annotation diagnostics

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.

Authors:Anthony Christidis [aut, cre], Andrew Ghazi [aut], Smriti Chawla [aut], Nitesh Turaga [ctb], Ludwig Geistlinger [aut], Robert Gentleman [aut]

scDiagnostics_1.1.0.tar.gz
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scDiagnostics_1.1.0.tgz(r-4.4-any)scDiagnostics_0.99.10.tgz(r-4.3-any)
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scDiagnostics_1.1.0.tgz(r-4.4-emscripten)scDiagnostics_0.99.10.tgz(r-4.3-emscripten)
scDiagnostics.pdf |scDiagnostics.html✨
scDiagnostics/json (API)
NEWS

# Install 'scDiagnostics' in R:

install.packages('scDiagnostics', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ccb-hms/scdiagnostics/issues

On BioConductor:scDiagnostics-1.1.0(bioc 3.21)scDiagnostics-1.0.0(bioc 3.20)

annotation classification clustering geneexpression rnaseq singlecell software transcriptomics

7.42 score 3 stars 46 scripts 29 exports 82 dependencies

Last updated 2 months agofrom:1b71ee2006. Checks:OK: 1 NOTE: 5 ERROR: 1. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 30 2024
R-4.5-win	NOTE	Nov 30 2024
R-4.5-linux	NOTE	Nov 30 2024
R-4.4-win	NOTE	Nov 30 2024
R-4.4-mac	NOTE	Nov 30 2024
R-4.3-win	NOTE	Sep 26 2024
R-4.3-mac	ERROR	Sep 26 2024

Exports:boxplotPCA calculateAveragePairwiseCorrelation calculateCategorizationEntropy calculateCellDistances calculateCellDistancesSimilarity calculateCellSimilarityPCA calculateCramerPValue calculateDiscriminantSpace calculateHotellingPValue calculateHVGOverlap calculateNearestNeighborProbabilities calculateSIRSpace calculateVarImpOverlap calculateWassersteinDistance compareCCA comparePCA comparePCASubspace detectAnomaly histQCvsAnnotation plotCellTypeMDS plotCellTypePCA plotGeneExpressionDimred plotGeneSetScores plotMarkerExpression plotPairwiseDistancesDensity plotQCvsAnnotation projectPCA projectSIR regressPC

Dependencies:abind askpass assorthead BH biglm Biobase BiocGenerics BiocNeighbors BiocParallel bluster boot cli cluster codetools colorspace cpp11 cramer crayon curl data.table DBI DelayedArray fansi farver formatR futile.logger futile.options generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggridges glue gtable httr igraph IRanges isoband isotree jsonlite labeling lambda.r lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats mgcv mime munsell nlme openssl patchwork pillar pkgconfig R6 ranger RColorBrewer Rcpp RcppEigen rlang S4Arrays S4Vectors scales SingleCellExperiment snow SparseArray speedglm SummarizedExperiment sys tibble transport UCSC.utils utf8 vctrs viridisLite withr XVector zlibbioc

Getting Started with scDiagnostics

Anthony Christidis, Andrew Ghazi, Smriti Chawla, Nitesh Turaga, Ludwig Geistlinger, Robert Gentleman

Rendered fromscDiagnostics.Rmdusingknitr::rmarkdownon Nov 30 2024.

Last update: 2024-10-25
Started: 2023-08-04

Visualization of Cell Type Annotations

Anthony Christidis, Andrew Ghazi, Smriti Chawla, Nitesh Turaga, Ludwig Geistlinger, Robert Gentleman

Rendered fromVisualizationTools.Rmdusingknitr::rmarkdownon Nov 30 2024.

Last update: 2024-10-25
Started: 2024-08-27

Evaluation of Dataset and Marker Gene Alignment

Anthony Christidis, Andrew Ghazi, Smriti Chawla, Nitesh Turaga, Ludwig Geistlinger, Robert Gentleman

Rendered fromDatasetMarkerGeneAlignment.Rmdusingknitr::rmarkdownon Nov 30 2024.

Last update: 2024-10-25
Started: 2024-08-27

Detection and Analysis of Annotation Anomalies

Anthony Christidis, Andrew Ghazi, Smriti Chawla, Nitesh Turaga, Ludwig Geistlinger, Robert Gentleman

Rendered fromAnnotationAnomalies.Rmdusingknitr::rmarkdownon Nov 30 2024.

Last update: 2024-10-25
Started: 2024-08-27

Help page	Topics
Plot Principal Components for Different Cell Types	boxplotPCA
Calculate Categorization Entropy	calculateCategorizationEntropy
Function to Calculate Bhattacharyya Coefficients and Hellinger Distances	calculateCellDistancesSimilarity
Calculate Cramer Test P-Values for Two-Sample Comparison of Multivariate ECDFs	calculateCramerPValue
Perform Hotelling's T-squared Test on PCA Scores for Single-cell RNA-seq Data	calculateHotellingPValue
Calculate the Overlap Coefficient for Highly Variable Genes	calculateHVGOverlap
Compare Gene Importance Across Datasets Using Random Forest	calculateVarImpOverlap
Compute Wasserstein Distances Between Query and Reference Datasets	calculateWassersteinDistance
Histograms: QC Stats and Annotation Scores Visualization	histQCvsAnnotation
Plot Reference and Query Cell Types using MDS	plotCellTypeMDS
Plot Principal Components for Different Cell Types	plotCellTypePCA
Visualize gene expression on a dimensional reduction plot	plotGeneExpressionDimred
Visualization of gene sets or pathway scores on dimensional reduction plot	plotGeneSetScores
Plot gene expression distribution from overall and cell type-specific perspective	plotMarkerExpression
Ridgeline Plot of Pairwise Distance Analysis	plotPairwiseDistancesDensity
Scatter plot: QC stats vs Cell Type Annotation Scores	plotQCvsAnnotation
Project Query Data Onto PCA Space of Reference Data	projectPCA
Project Query Data Onto SIR Space of Reference Data	projectSIR

Package: scDiagnostics 1.1.0

scDiagnostics: Cell type annotation diagnostics

Getting Started with scDiagnostics

Visualization of Cell Type Annotations

Evaluation of Dataset and Marker Gene Alignment

Detection and Analysis of Annotation Anomalies

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)