Plot the gene in reduced dimensional space.
plotGeneCount(curve, ...) # S4 method for SlingshotDataSet plotGeneCount( curve, counts = NULL, gene = NULL, clusters = NULL, models = NULL, title = NULL ) # S4 method for SingleCellExperiment plotGeneCount( curve, counts = NULL, gene = NULL, clusters = NULL, models = NULL, title = NULL ) # S4 method for CellDataSet plotGeneCount( curve, counts = NULL, gene = NULL, clusters = NULL, models = NULL, title = NULL )
One of three
The count matrix, genes in rows and cells in columns. Only needed
if the input is of the type
The name of gene for which you want to plot the count or the row
number of that gene in the count matrix. Alternatively, one can specify
The assignation of each cell to a cluster. Used to color the
The fitted GAMs, typically the output from
Title for the plot.
clusters arguments are supplied, the
plot will be colored according to gene count level. If none are provided, the
function will fail. When a
CellDataset object is provided as input,
the function relies on the
#>data(crv, package="tradeSeq") data(countMatrix, package="tradeSeq") rd <- slingshot::reducedDim(crv) cl <- kmeans(rd, centers = 7)$cluster lin <- slingshot::getLineages(rd, clusterLabels = cl, start.clus = 4)#>crv <- slingshot::getCurves(lin) counts <- as.matrix(countMatrix) gamList <- fitGAM(counts = counts, pseudotime = slingPseudotime(crv, na = FALSE), cellWeights = slingCurveWeights(crv)) plotGeneCount(crv, counts, gene = "Mpo")