Package: cydar 1.29.0

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'))

Uses libs:

c++– GNU Standard C++ Library v3

On BioConductor:cydar-1.29.0(bioc 3.20)cydar-1.28.0(bioc 3.19)

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

bioconductor-package

27 exports 0.82 score 91 dependencies 6 mentions

Last updated 2 months agofrom:bb6c3e1e62

Exports:cbind cellAssignments cellInformation cellIntensities countCells createColorBar dnaGate expandRadius findFirstSphere getCenterCell intensities intensityRanges interpretSpheres labelSpheres markernames medIntensities multiIntHist neighborDistances normalizeBatch outlierGate pickBestMarkers plotSphereIntensity plotSphereLogFC poolCells prepareCellData show spatialFDR

Dependencies:abind askpass base64enc BH Biobase BiocGenerics BiocNeighbors BiocParallel bslib cachem cli codetools colorspace commonmark cpp11 crayon curl cytolib DelayedArray digest fansi farver fastmap flowCore fontawesome formatR fs futile.logger futile.options GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue gridExtra gtable htmltools httpuv httr IRanges isoband jquerylib jsonlite labeling lambda.r later lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime munsell nlme openssl pillar pkgconfig promises R6 rappdirs RColorBrewer Rcpp RcppHNSW Rhdf5lib rlang RProtoBufLib S4Arrays S4Vectors sass scales shiny SingleCellExperiment snow sourcetools SparseArray SummarizedExperiment sys tibble UCSC.utils utf8 vctrs viridis viridisLite withr xtable XVector zlibbioc

Detecting differentially abundant subpopulations in mass cytometry data

Aaron Lun

Rendered fromcydar.Rmdusingknitr::rmarkdownon Jun 15 2024.

Last update: 2020-04-02
Started: 2017-03-27

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Count cells in high-dimensional space	countCells
Create a color bar	createColorBar
CyData class and methods	cbind,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 channels	dnaGate
Expand the hypersphere radius	expandRadius
Identifies the first non-redundant hyperspheres	findFirstSphere
Define intensity ranges	intensityRanges
Interactive interpretation of hyperspheres	interpretSpheres
Label unannotated hyperspheres	labelSpheres
Compute median marker intensities	medIntensities
multiIntHist	multiIntHist
Compute distances to neighbors	neighborDistances
Normalize intensities across batches	normalizeBatch
Create an outlier gate	outlierGate
Pick best markers	pickBestMarkers
Plot cell or hypersphere data	plotSphereIntensity
Plot changes in hypersphere abundance	plotSphereLogFC
Pool cells for pre-processing	poolCells
Prepare mass cytometry data	prepareCellData
Compute the spatial FDR	spatialFDR