plotMarker: Plot Cell-Type-Specific Gene Markers

In roryk/bcbioSinglecell: Single-Cell RNA-Seq Utilities

Description

Plot gene expression per cell in multiple formats:

1. plotMarkerTSNE(): t-SNE gene expression plot.

2. plotDot(): Dot plot.

3. plotViolin(): Violin plot.

Usage

plotKnownMarkersDetected(object, ...)

plotMarkerTSNE(object, ...)

plotMarkerUMAP(object, ...)

plotTopMarkers(object, ...)

## S4 method for signature 'SingleCellExperiment'
plotMarkerTSNE(object, genes,
  expression = c("mean", "median", "sum"), color = NULL,
  pointsAsNumbers = FALSE, pointSize = 0.75, pointAlpha = 0.8,
  label = TRUE, labelSize = 6L, dark = FALSE, grid = FALSE,
  legend = TRUE, aspectRatio = 1L, title = TRUE)

## S4 method for signature 'seurat'
plotMarkerTSNE(object, genes, expression = c("mean",
  "median", "sum"), color = NULL, pointsAsNumbers = FALSE,
  pointSize = 0.75, pointAlpha = 0.8, label = TRUE, labelSize = 6L,
  dark = FALSE, grid = FALSE, legend = TRUE, aspectRatio = 1L,
  title = TRUE)

## S4 method for signature 'SingleCellExperiment'
plotMarkerUMAP(object, genes,
  expression = c("mean", "median", "sum"), color = NULL,
  pointsAsNumbers = FALSE, pointSize = 0.75, pointAlpha = 0.8,
  label = TRUE, labelSize = 6L, dark = FALSE, grid = FALSE,
  legend = TRUE, aspectRatio = 1L, title = TRUE)

## S4 method for signature 'seurat'
plotMarkerUMAP(object, genes, expression = c("mean",
  "median", "sum"), color = NULL, pointsAsNumbers = FALSE,
  pointSize = 0.75, pointAlpha = 0.8, label = TRUE, labelSize = 6L,
  dark = FALSE, grid = FALSE, legend = TRUE, aspectRatio = 1L,
  title = TRUE)

## S4 method for signature 'SingleCellExperiment'
plotTopMarkers(object, markers,
  reduction = c("TSNE", "UMAP"), headerLevel = 2L, ...)

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

## S4 method for signature 'SingleCellExperiment'
plotKnownMarkersDetected(object, markers,
  reduction = c("TSNE", "UMAP"), headerLevel = 2L, ...)

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

Arguments

object	Object.
...	Additional arguments.
genes	Gene identifiers. Must match the rownames of the object.
expression	Calculation to apply. Uses match.arg() and defaults to the first argument in the vector.
color	Desired ggplot color scale. Must supply discrete values. When set to NULL, the default ggplot2 color palette will be used. If manual color definitions are desired, we recommend using ggplot2::scale_color_manual().
pointsAsNumbers	Plot the points as numbers (TRUE) or dots (FALSE).
pointSize	Cell point size.
pointAlpha	Alpha transparency level. Useful when there many cells in the dataset, and some cells can be masked.
label	Overlay a cluster identitiy label on the plot.
labelSize	Size of the text label.
dark	Plot against a dark background using basejump::theme_midnight().
grid	Show major grid lines but hide axis lines.
legend	Include plot legend.
aspectRatio	Aspect ratio.
title	Plot title.
markers	grouped_df of marker genes. plotTopMarkers(): must be grouped by "cluster". plotKnownMarkersDetected(): must be grouped by "cellType".
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.

Plot top markers

The number of markers to plot is determined by the output of the topMarkers() function. If you want to reduce the number of genes to plot, simply reassign first using that function. If necessary, we can add support for the number of genes to plot here in a future update.

Author(s)

Michael Steinbaugh, Rory Kirchner

See Also

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

Examples

object <- seurat_small
title <- "mito genes"
genes <- grep("^MT-", rownames(object), value = TRUE)
print(genes)

# t-SNE
plotMarkerTSNE(
    object = object,
    genes = genes,
    title = title
)

# Dark mode
plotMarkerTSNE(
    object = object,
    genes = genes,
    dark = TRUE,
    title = title
)

# Number cloud
plotMarkerTSNE(
    object = object,
    genes = genes,
    pointsAsNumbers = TRUE,
    title = title
)

# UMAP
plotMarkerUMAP(
    object = object,
    genes = genes,
    title = title
)

# Top markers
markers <- topMarkers(all_markers_small, n = 1)
markers
plotTopMarkers(object, markers = tail(markers, 1))

# Known markers detected
markers <- head(known_markers_small, n = 1)
markers
plotKnownMarkersDetected(object, markers = head(markers, 1))

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