Create a scatterplot for each row of a normalized
gene expression matrix where x and y axis are from a
data dimension reduction tool.
The cells are colored by "celda_cell_cluster" column in
colData(altExp(x, altExpName))
if x
is a
SingleCellExperiment object, or x
if x
is
a integer vector of cell cluster labels.
plotDimReduceCluster( x, reducedDimName, altExpName = "featureSubset", dim1 = NULL, dim2 = NULL, size = 0.5, xlab = NULL, ylab = NULL, specificClusters = NULL, labelClusters = FALSE, groupBy = NULL, labelSize = 3.5 ) # S4 method for SingleCellExperiment plotDimReduceCluster( x, reducedDimName, altExpName = "featureSubset", dim1 = 1, dim2 = 2, size = 0.5, xlab = NULL, ylab = NULL, specificClusters = NULL, labelClusters = FALSE, groupBy = NULL, labelSize = 3.5 ) # S4 method for vector plotDimReduceCluster( x, dim1, dim2, size = 0.5, xlab = "Dimension_1", ylab = "Dimension_2", specificClusters = NULL, labelClusters = FALSE, groupBy = NULL, labelSize = 3.5 )
x | Integer vector of cell cluster labels or a
SingleCellExperiment object
containing cluster labels for each cell in |
---|---|
reducedDimName | The name of the dimension reduction slot in
|
altExpName | The name for the altExp slot to use. Default "featureSubset". |
dim1 | Integer or numeric vector. If |
dim2 | Integer or numeric vector. If |
size | Numeric. Sets size of point on plot. Default |
xlab | Character vector. Label for the x-axis. Default |
ylab | Character vector. Label for the y-axis. Default |
specificClusters | Numeric vector.
Only color cells in the specified clusters.
All other cells will be grey.
If NULL, all clusters will be colored. Default |
labelClusters | Logical. Whether the cluster labels are plotted. Default FALSE. |
groupBy | Character vector. Contains sample labels for each cell. If NULL, all samples will be plotted together. Default NULL. |
labelSize | Numeric. Sets size of label if labelClusters is TRUE. Default 3.5. |
The plot as a ggplot object
data(sceCeldaCG) sce <- celdaTsne(sceCeldaCG) plotDimReduceCluster(x = sce, reducedDimName = "celda_tSNE", specificClusters = c(1, 2, 3))library(SingleCellExperiment) data(sceCeldaCG, celdaCGMod) sce <- celdaTsne(sceCeldaCG) plotDimReduceCluster(x = celdaClusters(celdaCGMod)$z, dim1 = reducedDim(altExp(sce), "celda_tSNE")[, 1], dim2 = reducedDim(altExp(sce), "celda_tSNE")[, 2], specificClusters = c(1, 2, 3))