Package: scDiagnostics 0.99.11
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:
scDiagnostics_0.99.11.tar.gz
scDiagnostics_0.99.11.zip(r-4.5)scDiagnostics_0.99.11.zip(r-4.4)scDiagnostics_0.99.10.zip(r-4.3)
scDiagnostics_0.99.11.tgz(r-4.4-any)scDiagnostics_0.99.10.tgz(r-4.3-any)
scDiagnostics_0.99.11.tar.gz(r-4.5-noble)scDiagnostics_0.99.11.tar.gz(r-4.4-noble)
scDiagnostics_0.99.11.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-0.99.10(bioc 3.20)
annotationclassificationclusteringgeneexpressionrnaseqsinglecellsoftwaretranscriptomics
Last updated 5 days agofrom:c58572e51c. Checks:OK: 1 ERROR: 1 NOTE: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 26 2024 |
R-4.5-win | NOTE | Oct 26 2024 |
R-4.5-linux | NOTE | Oct 26 2024 |
R-4.4-win | NOTE | Oct 26 2024 |
R-4.4-mac | NOTE | Oct 26 2024 |
R-4.3-win | NOTE | Sep 26 2024 |
R-4.3-mac | ERROR | Sep 26 2024 |
Exports:boxplotPCAcalculateAveragePairwiseCorrelationcalculateCategorizationEntropycalculateCellDistancescalculateCellDistancesSimilaritycalculateCellSimilarityPCAcalculateCramerPValuecalculateDiscriminantSpacecalculateHotellingPValuecalculateHVGOverlapcalculateNearestNeighborProbabilitiescalculateSIRSpacecalculateVarImpOverlapcalculateWassersteinDistancecompareCCAcomparePCAcomparePCASubspacedetectAnomalyhistQCvsAnnotationplotCellTypeMDSplotCellTypePCAplotGeneExpressionDimredplotGeneSetScoresplotMarkerExpressionplotPairwiseDistancesDensityplotQCvsAnnotationprojectPCAprojectSIRregressPC
Dependencies:abindaskpassassortheadBHbiglmBiobaseBiocGenericsBiocNeighborsBiocParallelblusterbootcliclustercodetoolscolorspacecpp11cramercrayoncurldata.tableDBIDelayedArrayfansifarverformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggridgesgluegtablehttrigraphIRangesisobandisotreejsonlitelabelinglambda.rlatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpatchworkpillarpkgconfigR6rangerRColorBrewerRcppRcppEigenrlangS4ArraysS4VectorsscalesSingleCellExperimentsnowSparseArrayspeedglmSummarizedExperimentsystibbletransportUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc
Getting Started with scDiagnostics
Rendered fromscDiagnostics.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2024-10-25
Started: 2023-08-04
Visualization of Cell Type Annotations
Rendered fromVisualizationTools.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2024-10-25
Started: 2024-08-27
Evaluation of Dataset and Marker Gene Alignment
Rendered fromDatasetMarkerGeneAlignment.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2024-10-25
Started: 2024-08-27
Detection and Analysis of Annotation Anomalies
Rendered fromAnnotationAnomalies.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2024-10-25
Started: 2024-08-27