plotClusterExprs: Plot expression distributions by cluster
In CATALYST: Cytometry dATa anALYSis Tools

Description Usage Arguments Value Author(s) References Examples

Plots smoothed densities of marker intensities by cluster.

1	plotClusterExprs(x, k = "meta20", features = "type")

`x`	a `SingleCellExperiment`.
`k`	character string specifying which clustering to use; valid values are `names(cluster_codes(x))`.
`features`	a character vector specifying which antigens to include; valid values are `"type"/"state"` for `type/state_markers(x)` if `rowData(x)$marker_class` have been specified; a subset of `rownames(x)`; NULL to use all features.

a ggplot object.

Helena L Crowell helena.crowell@uzh.ch

Nowicka M, Krieg C, Crowell HL, Weber LM et al. CyTOF workflow: Differential discovery in high-throughput high-dimensional cytometry datasets. F1000Research 2017, 6:748 (doi: 10.12688/f1000research.11622.1)

# construct SCE & run clustering
data(PBMC_fs, PBMC_panel, PBMC_md)
sce <- prepData(PBMC_fs, PBMC_panel, PBMC_md)
sce <- cluster(sce)

plotClusterExprs(sce, k = "meta8")