Create ternary simplex plot with SingleCellExperiment objects

Create ternary plots that show similarity between single cells and selected three terminals in a ternary baricentric coordinate.

Usage

# S3 method for class 'SingleCellExperiment'
plotTernary(
  x,
  assay.type = "counts",
  clusterVar = NULL,
  processed = FALSE,
  dotColorBy = NULL,
  legendTitle = NULL,
  ...
)

Arguments

x

A SingleCellExperiment object.

assay.type

Assay to use for calculating the similarity. Default "counts".

clusterVar

A variable name in colData(x). Default NULL uses colLabels(x).

processed

Logical. Whether the input matrix is already processed. TRUE will bypass internal preprocessing and input matrix will be directly used for similarity calculation. Default FALSE and raw count input is recommended. If missing in call, using slot = "counts" in "Seurat" method or using assay.type = "counts" in "SingleCellExperiment" method will force this argument to be FALSE and others for TRUE.

dotColorBy

A vector/factor for coloring dots, can be either categorical (must be character or factor) or continuous. Default NULL.

legendTitle

Title on the legend/colorbar. Default NULL uses "cluster" if dotColorBy is missing (default); user-end variable expression if dotColorBy is directly specified from plotQuaternary.default method; variable name if dotColorBy is specified from Seurat or SingleCellExperiment method.

...

Arguments passed on to plotTernary.default, plotTernary.simMat

vertices: Vector of three unique cluster names that will be used for plotting. Or a named list that groups clusters as three terminal vertices. There must not be any overlap between groups.
features: Valid matrix row subsetting index to select features for similarity calculation. Default NULL uses all available features.
byCluster: Default NULL to generate one plot with all cells. Set "all" to split cells in plot by cluster and returns a list of subplots for each cluster as well as the plot including all cells. Otherwise, a vector of cluster names to generate a list of subplots for the specified clusters.
veloGraph: Cell x cell dgCMatrix object containing velocity information. Shows velocity grid-arrow layer when specified. Default NULL does not show velocity.
method: Similarity calculation method. Default "euclidean". Choose from "euclidean", "cosine", "pearson", "spearman".
force: Whether to force calculate the similarity when more then 500 features are detected, which is generally not recommended. Default FALSE.
sigma: Gaussian kernel parameter that controls the effect of variance. Only effective when using a distance metric (i.e. method is "euclidian" or "cosine"). Larger values tighten the dot spreading on figure. Default 0.08.
scale: Whether to min-max scale the distance matrix by clusters. Default TRUE.
dotColor: Character vector of color codes. When dotColorBy is NULL, use one or as many colors as the number of cells. If dotColorBy is categorical, specify as many colors as the number of categories in dotColorBy or ggplot2 categorical color palette is used by default. If dotColorBy is continuous, specify together with breaks argument.
palette: Color palette to use when dotColorBy is given. Default "D" (viridis) for continuous value and ggplot2 default for categorical value. See detail for alternatives.
direction: Sets the order of colors in the scale. Default 1 orders as palette default. If -1, the order of colors is reversed.
breaks: Number of breaks for continuous color scale passed to non-interactive "plot3D::scatter3D" call. Default NULL.
returnData: Logical. Whether to return similarity and aggregated velocity data if applicable instead of generating plot. Default FALSE.
title: Title text of the plot. Default NULL.
nGrid: Number of grids along the bottom side of the equilateral triangle. Default 10.
radius: Arrow length of unit velocity. Lower this when arrows point outside of the coordinate. Default 0.1.
dotSize: Dot aesthetics passed to geom_point. Default 0.6 when not interactive, 4 when interactive.
dotShuffle: Whether to shuffle the order of dots being added to the plot, useful when categorical colors are used and mixing of categories is expected. Default NULL does shuffle when dotColorBy given is categorical and does not otherwise.
labelColors: Colors of the axis lines and vertex labels. Default c("#3B4992FF", "#EE0000FF", "#008B45FF") (blue, red and green)
vertexLabelSize: Size of vertex labels. Default 6 when not interactive, 16 when interactive.
vertexLabelDrift: Position adjustment of the vertex labels, only applied to non-interactive view. Default 0.03.
axisBreak: Number of breaks to be labeled along axis. Default 5.
axisTextShow: Logical, whether to show axis text. Default TRUE.
axisTextSize: Size of text along each axis break. Default 4 for non-interactive view, 12 for interactive view.
axisTextDrift: Position adjustment of the axis text, only applied to non-interactive view. Default 0.01.
gridLineAlpha: Transparency of background grid lines. Default 0.6.
arrowLinewidth: Line width of the velocity arrows. Default 0.25 for non-interactive view, 2 for interactive view.
arrowAngle: Controls the angle of the arrowhead, only applied to non-interactive view. Default 20.
arrowLen: Control length in centimetre from arrow tip to arrow tail, only applied to non-interactive view. Default 0.2.
titleSize: Size of title text. Default 14 for non-interactive view, 20 for interactive view.
equilateral: Logical, whether to always display the triangle as equilateral. Default TRUE.
margin: Margin allowed around of the triangle plotting region when equilateral = TRUE
interactive: Logical. Whether to display plotly interactive view. Default FALSE.

Value

By default, a "ggplot" object when byCluster is not specified, a list of "ggplot" object when byCluster is specified. When interactive = TRUE, a "plotly" object is returned. When returnData = TRUE, a list of similarity matrix and aggregated velocity matrix is returned.

Examples

# \donttest{
# SingleCellExperiment example
library(SingleCellExperiment)
sce <- SingleCellExperiment(assays = list(counts = rnaRaw))
colLabels(sce) <- rnaCluster
gene <- selectTopFeatures(sce, vertices = c("OS", "RE", "CH"))
#> Selected 30 features for "CH".
#> Selected 30 features for "OS".
#> Selected 30 features for "RE".
plotTernary(sce, features = gene, vertices = c("OS", "RE", "CH"))

# }

Usage

Arguments

Value

See also

Examples