R/runTSCAN.R
plotTSCANDimReduceFeatures.Rd
A wrapper function which plots all cells or cells in chosen cluster. Each point is a cell colored by the expression of a feature of interest, the relevant edges of the MST are overlaid on top.
plotTSCANDimReduceFeatures(
inSCE,
features,
useReducedDim = "UMAP",
useAssay = "logcounts",
by = "rownames",
useCluster = NULL,
featureDisplay = metadata(inSCE)$featureDisplay,
combinePlot = c("all", "none")
)
Input SingleCellExperiment object.
Choose the feature of interest to explore the expression level on the trajectory. Required.
A single character for the matrix of 2D embedding.
Should exist in reducedDims
slot. Default "UMAP"
.
A single character for the feature expression matrix. Should
exist in assayNames(inSCE)
. Default "logcounts"
.
Where should features
be found? NULL
,
"rownames"
for rownames(inSCE)
, otherwise will be regarded as
rowData
variable.
Choose specific clusters where gene expression needs to be
visualized. By default NULL
, all clusters are chosen.
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.
Must be either "all"
or "none"
. "all"
will combine plots of each feature into a single .ggplot
object,
while "none"
will output a list of plots. Default "all"
.
A .ggplot
object of cell scatter plot, colored by the
expression of a gene of interest, with the layer of trajectory.
data("mouseBrainSubsetSCE", package = "singleCellTK")
mouseBrainSubsetSCE <- runTSCAN(inSCE = mouseBrainSubsetSCE,
useReducedDim = "PCA_logcounts")
#> Sat Mar 18 10:30:11 2023 ... Running 'scran SNN clustering' with 'louvain' algorithm
#> Sat Mar 18 10:30:12 2023 ... Identified 2 clusters
#> Sat Mar 18 10:30:12 2023 ... Running TSCAN to estimate pseudotime
#> Sat Mar 18 10:30:12 2023 ... Clusters involved in path index 2 are: 1, 2
#> Sat Mar 18 10:30:12 2023 ... Number of estimated paths is 1
plotTSCANDimReduceFeatures(inSCE = mouseBrainSubsetSCE,
features = "Tshz1",
useReducedDim = "TSNE_logcounts")