runTSCANClusterDEAnalysis
on
cell 2D embedding with MST overlaidR/runTSCAN.R
plotTSCANClusterDEG.Rd
A wrapper function which plot the top features expression
identified by runTSCANClusterDEAnalysis
on the 2D embedding of
the cells cluster used in the analysis. The related MST edges are overlaid.
plotTSCANClusterDEG(
inSCE,
useCluster,
pathIndex = NULL,
useReducedDim = "UMAP",
topN = 9,
useAssay = NULL,
featureDisplay = metadata(inSCE)$featureDisplay,
combinePlot = c("all", "none")
)
Input SingleCellExperiment object.
Choose a cluster used for identifying DEG with
runTSCANClusterDEAnalysis
. Required.
Specifies one of the branching paths from useCluster
and plot the top DEGs on this path. Ususally presented by the terminal
cluster of a path. By default NULL
plot top DEGs of all paths.
A single character for the matrix of 2D embedding.
Should exist in reducedDims
slot. Default "UMAP"
.
Integer. Use top N genes identified. Default 9
.
A single character for the feature expression matrix. Should
exist in assayNames(inSCE)
. Default NULL
for using the one used
in runTSCANClusterDEAnalysis
.
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 identified by runTSCANClusterDEAnalysis
,
with the layer of trajectory.
data("mouseBrainSubsetSCE", package = "singleCellTK")
mouseBrainSubsetSCE <- runTSCAN(inSCE = mouseBrainSubsetSCE,
useReducedDim = "PCA_logcounts")
#> Sat Mar 18 10:30:05 2023 ... Running 'scran SNN clustering' with 'louvain' algorithm
#> Sat Mar 18 10:30:06 2023 ... Identified 2 clusters
#> Sat Mar 18 10:30:06 2023 ... Running TSCAN to estimate pseudotime
#> Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
#> Also defined by ‘spam’
#> Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
#> Also defined by ‘spam’
#> Sat Mar 18 10:30:06 2023 ... Clusters involved in path index 2 are: 1, 2
#> Sat Mar 18 10:30:06 2023 ... Number of estimated paths is 1
mouseBrainSubsetSCE <- runTSCANClusterDEAnalysis(inSCE = mouseBrainSubsetSCE,
useCluster = 1)
#> Sat Mar 18 10:30:06 2023 ... Finding DEG between TSCAN branches
#> Sat Mar 18 10:30:06 2023 ... Clusters involved in path index 2 are: 1, 2
plotTSCANClusterDEG(mouseBrainSubsetSCE, useCluster = 1,
useReducedDim = "TSNE_logcounts")