plotCellTypesPerCluster: Plot Cell Types per Cluster
In WeiSong-bio/roryk-bcbioSinglecell: Single-Cell RNA-Seq Utilities

Description Usage Arguments Value Author(s) See Also Examples

Plot the geometric mean of the significant marker genes for every known cell type (per unbiased cluster). Cell types with too few (min cutoff) or too many (max cutoff) marker genes will be skipped.

plotCellTypesPerCluster(object, ...)

## S4 method for signature 'seurat'
plotCellTypesPerCluster(object, cellTypesPerCluster,
  reduction = c("TSNE", "UMAP"), headerLevel = 2L, ...)

`object`	Object.
`...`	Passthrough arguments to `plotMarkerTSNE()` or `plotMarkerUMAP()`.
`cellTypesPerCluster`	Cell types per cluster `grouped_df`. This must be the return from `cellTypesPerCluster()`.
`reduction`	Dimensional reduction method to apply. Defaults to t-SNE ("`TSNE`") but UMAP is also supported ("`UMAP`").
`headerLevel`	R Markdown header level.

Show graphical output. Invisibly return ggplot list.

Michael Steinbaugh

Other Clustering Functions: cellTypesPerCluster, knownMarkersDetected, plotFeatureTSNE, plotKnownMarkersDetected, plotPCElbow, plotTSNE, sanitizeMarkers, topMarkers

# seurat ====
per_cluster <- cellTypesPerCluster(known_markers_small)
glimpse(per_cluster)

# Let's plot the first row, as an example
plotCellTypesPerCluster(
    object = seurat_small,
    cellTypesPerCluster = head(per_cluster, 1),
)