plotCellTypesPerCluster: Plot Cell Types per Cluster

Description Usage Arguments Value Author(s) See Also Examples

Description

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.

Usage

1
2
3
4
5
plotCellTypesPerCluster(object, ...)

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

Arguments

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.

Value

Show graphical output. Invisibly return ggplot list.

Author(s)

Michael Steinbaugh

See Also

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

Examples

1
2
3
4
5
6
7
8
9
# 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),
)

roryk/bcbioSinglecell documentation built on May 27, 2019, 10:44 p.m.