Plot expression changes of top features along a TSCAN pseudotime path

Source: R/runTSCAN.R

A wrapper function which visualizes outputs from the runTSCANDEG function. Plots the genes that increase or decrease in expression with increasing pseudotime along the path in the MST. runTSCANDEG has to be run in advance with using the same pathIndex of interest.

plotTSCANPseudotimeGenes(
  inSCE,
  pathIndex,
  direction = c("increasing", "decreasing"),
  topN = 10,
  useAssay = NULL,
  featureDisplay = metadata(inSCE)$featureDisplay
)

Arguments

inSCE

Input SingleCellExperiment object.

pathIndex

Path index for which the pseudotime values should be used. Should have being used in runTSCANDEG.

direction

Should we show features with expression increasing or decreeasing along the increase in TSCAN pseudotime? Choices are "increasing" or "decreasing".

topN

An integer. Only to plot this number of top genes that are increasing/decreasing in expression with increasing pseudotime along the path in the MST. Default 10

useAssay

A single character to specify a feature expression matrix in assays slot. The expression of top features from here will be visualized. Default NULL use the one used for runTSCANDEG.

featureDisplay

Specify the feature ID type to display. Users can set default value with setSCTKDisplayRow. NULL or "rownames" specifies the rownames of inSCE. Other character values indicates rowData variable.

Value

A .ggplot object with the facets of the top genes. Expression on y-axis, pseudotime on x-axis.

Author

Nida Pervaiz

Examples

data("mouseBrainSubsetSCE", package = "singleCellTK")
mouseBrainSubsetSCE <- runTSCAN(inSCE = mouseBrainSubsetSCE,
                                useReducedDim = "PCA_logcounts")
#> Sat Mar 18 10:30:13 2023 ... Running 'scran SNN clustering' with 'louvain' algorithm
#> Sat Mar 18 10:30:14 2023 ...   Identified 2 clusters
#> Sat Mar 18 10:30:14 2023 ... Running TSCAN to estimate pseudotime
#> Sat Mar 18 10:30:14 2023 ...   Clusters involved in path index 2 are: 1, 2
#> Sat Mar 18 10:30:14 2023 ...   Number of estimated paths is 1
terminalNodes <- listTSCANTerminalNodes(mouseBrainSubsetSCE)
mouseBrainSubsetSCE <- runTSCANDEG(inSCE = mouseBrainSubsetSCE,
                                   pathIndex = terminalNodes[1])
plotTSCANPseudotimeGenes(mouseBrainSubsetSCE,
                         pathIndex = terminalNodes[1],
                         useAssay = "logcounts")