Package: cydar 1.31.0

Aaron Lun

cydar: Using Mass Cytometry for Differential Abundance Analyses

Identifies differentially abundant populations between samples and groups in mass cytometry data. Provides methods for counting cells into hyperspheres, controlling the spatial false discovery rate, and visualizing changes in abundance in the high-dimensional marker space.

Authors:Aaron Lun [aut, cre]

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NEWS

# Install 'cydar' in R:
install.packages('cydar', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On BioConductor:cydar-1.31.0(bioc 3.21)cydar-1.30.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologyflowcytometrymultiplecomparisonproteomicssinglecellcpp

5.64 score 48 scripts 217 downloads 6 mentions 27 exports 92 dependencies

Last updated 2 months agofrom:8dc413ed52. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 10 2024
R-4.5-win-x86_64NOTEDec 10 2024
R-4.5-linux-x86_64NOTEDec 10 2024
R-4.4-win-x86_64NOTEDec 10 2024
R-4.4-mac-x86_64NOTEDec 10 2024
R-4.4-mac-aarch64NOTEDec 10 2024
R-4.3-win-x86_64NOTEDec 10 2024
R-4.3-mac-x86_64NOTEDec 10 2024
R-4.3-mac-aarch64NOTEDec 10 2024

Exports:cbindcellAssignmentscellInformationcellIntensitiescountCellscreateColorBardnaGateexpandRadiusfindFirstSpheregetCenterCellintensitiesintensityRangesinterpretSphereslabelSpheresmarkernamesmedIntensitiesmultiIntHistneighborDistancesnormalizeBatchoutlierGatepickBestMarkersplotSphereIntensityplotSphereLogFCpoolCellsprepareCellDatashowspatialFDR

Dependencies:abindaskpassassortheadbase64encBHBiobaseBiocGenericsBiocNeighborsBiocParallelbslibcachemclicodetoolscolorspacecommonmarkcpp11crayoncurlcytolibDelayedArraydigestfansifarverfastmapflowCorefontawesomeformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegridExtragtablehtmltoolshttpuvhttrIRangesisobandjquerylibjsonlitelabelinglambda.rlaterlatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigpromisesR6rappdirsRColorBrewerRcppRhdf5librlangRProtoBufLibS4ArraysS4VectorssassscalesshinySingleCellExperimentsnowsourcetoolsSparseArraySummarizedExperimentsystibbleUCSC.utilsutf8vctrsviridisviridisLitewithrxtableXVectorzlibbioc

Detecting differentially abundant subpopulations in mass cytometry data

Rendered fromcydar.Rmdusingknitr::rmarkdownon Dec 10 2024.

Last update: 2024-09-06
Started: 2017-03-27

Readme and manuals

Help Manual

Help pageTopics
Count cells in high-dimensional spacecountCells
Create a color barcreateColorBar
CyData class and methodscbind,CyData-method cellAssignments cellInformation cellIntensities CyData CyData-class getCenterCell intensities markernames markernames,CyData-method show,CyData-method [,CyData,ANY,ANY,ANY-method [<-,CyData,ANY,ANY,CyData-method
Gate events based on DNA channelsdnaGate
Expand the hypersphere radiusexpandRadius
Identifies the first non-redundant hyperspheresfindFirstSphere
Define intensity rangesintensityRanges
Interactive interpretation of hyperspheresinterpretSpheres
Label unannotated hypersphereslabelSpheres
Compute median marker intensitiesmedIntensities
multiIntHistmultiIntHist
Compute distances to neighborsneighborDistances
Normalize intensities across batchesnormalizeBatch
Create an outlier gateoutlierGate
Pick best markerspickBestMarkers
Plot cell or hypersphere dataplotSphereIntensity
Plot changes in hypersphere abundanceplotSphereLogFC
Pool cells for pre-processingpoolCells
Prepare mass cytometry dataprepareCellData
Compute the spatial FDRspatialFDR