tsneByMeanMarkerExpression: Colour cells in t-SNE or PCA space by gene expression
In fungenomics/cytobox: A toolbox for analyzing single cell RNA-seq data

Description Usage Arguments Value Functions Author(s) Examples

Plot a low-dimensional embedding of the cells, coloured by expression of a gene, or mean expression of a group of marker genes. Defaults to t-SNE space, but see the reduction argument for how to plot in PCA space instead. This function is based on Seurat::FeaturePlot.

tsneByMeanMarkerExpression(seurat, genes, reduction = "tsne",
  label = TRUE, palette = "redgrey", title = NULL, alpha = 0.6,
  label_repel = TRUE, label_size = 4, legend = TRUE,
  hide_ticks = FALSE, hide_axes = FALSE, limits = NULL,
  label_short = FALSE, dim1 = 1, dim2 = 2, return_df = FALSE,
  point_size = 1)

feature(seurat, genes, per_gene = TRUE, statistic = "mean",
  label = TRUE, palette = "redgrey", label_repel = FALSE,
  label_size = 4, label_short = FALSE, legend = FALSE,
  title = NULL, reduction = "tsne", limits = c(NA, NA), dim1 = 1,
  dim2 = 2, alpha = ifelse(statistic == "percentiles", FALSE, 0.6),
  point_size = 0.5, ncol = ifelse(length(genes) == 1, 1,
  ifelse(length(genes) %in% c(2, 4), 2, 3)), hide_ticks = TRUE,
  hide_axes = TRUE)

`seurat`	Seurat object, where dimensionality reduction has been applied, i.e. (after applying Seurat::RunPCA() or Seurat::RunTSNE() to the object)
`genes`	String or character vector specifying gene(s) to use
`reduction`	String specifying the dimensionality reduction to use, retrieves t-SNE by default. This should match the names of the elements of the list seurat@dr, so it will typically be one of "pca" or "tsne". Default: "tsne"
`label`	Logical, whether to label clusters on the plot. Default: TRUE.
`palette`	String or character vector. If a string, one of "viridis", "blues", or "redgrey", specifying which gradient palette to use. Otherwise, a character vector of colours (from low to high) to interpolate to create the scael. Default: redgrey.
`title`	(Optional) String specifying the plot title
`alpha`	Numeric, fixed alpha for points. Default: 0.6
`label_repel`	Logical, if `label` is TRUE, whether to plot cluster labels repelled from the center, on a slightly transparent white background and with an arrow pointing to the cluster center. If FALSE, simply plot the cluster label at the cluster center. Default: TRUE.
`label_size`	Numeric, controls the size of text labels. Default: 4.
`legend`	Logical, whether or not to plot legend. Default: TRUE
`hide_ticks`	Logical, whether to hide axis ticks. Default: FALSE
`hide_axes`	Logical, whether to hide axis labels. Default: TRUE
`limits`	(Optional) A numeric vector of length two providing the limits to use for the colour scale (documentation from `continous_scale`. Default: 0 and max of the data.
`label_short`	(Optional/Experimental!!) Logical, if TRUE, assumes clusters (at seurat@ident) consist of a prefix and a suffix separated by a non-alpha numeric character (`"[^[:alnum:]]+"`), and tries to separate these names and only plot the prefix, for shorter labels and a cleaner plot. Default: FALSE.
`dim1`	Numeric, index of dimension from `reduction` to plot on the x-axis. e.g. to plot the 3rd PC on the x-axis, pass 3. Default: 1.
`dim2`	Numeric, like `dim2`, but for the y-axis. Default: 2.
`point_size`	Numeric, size of points in scatterplot. Default: 1. (A smaller value around 0.5 is better for plots which will be viewed at small scale.)

A ggplot object

feature: Shortcut function for plotting mean expression

Selin Jessa

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tsneByMeanMarkerExpression(pbmc, "IL32")
tsneByMeanMarkerExpression(pbmc, c("IL32", "CD2"), reduction = "pca")
tsneByMeanMarkerExpression(pbmc, "IL32", reduction = "pca", dim1 = 1, dim2 = 3)