R: Differential discovery in high-dimensional cytometry via high-resolution clustering

# Differential discovery in high-dimensional cytometry via high-resolution clustering

## Documentation for package ‘diffcyt’ version 1.32.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

diffcyt-package | Run 'diffcyt' pipeline
calcCounts | Calculate cluster cell counts
calcMedians | Calculate cluster medians
calcMediansByClusterMarker | Calculate medians (by cluster and marker)
calcMediansBySampleMarker | Calculate medians (by sample and marker)
createContrast | Create contrast matrix
createDesignMatrix | Create design matrix
createFormula | Create model formula and corresponding data frame of variables
diffcyt | Run 'diffcyt' pipeline
generateClusters | Generate clusters
plotHeatmap | Plot heatmap
prepareData | Prepare data
testDA_edgeR | Test for differential abundance: method 'diffcyt-DA-edgeR'
testDA_GLMM | Test for differential abundance: method 'diffcyt-DA-GLMM'
testDA_voom | Test for differential abundance: method 'diffcyt-DA-voom'
testDS_limma | Test for differential states: method 'diffcyt-DS-limma'
testDS_LMM | Test for differential states: method 'diffcyt-DS-LMM'
topClusters | Alias for 'topTable' (deprecated)
topTable | Show table of results for top clusters or cluster-marker combinations
transformData | Transform data