Constructs a phylogenetic tree relating the 'average' cell from each identity class. Tree is estimated based on a distance matrix constructed in either gene expression space or PCA space.
BuildClusterTree(object, features = NULL, dims = NULL, graph = NULL,
slot = "data", reorder = FALSE, reorder.numeric = FALSE,
verbose = TRUE)Seurat object
Genes to use for the analysis. Default is the set of
variable genes (VariableFeatures(object = object))
If set, tree is calculated in PCA space; overrides features
If graph is passed, build tree based on graph connectivity between
clusters; overrides dims and features
Slot to use; will be overriden by use.scale and use.counts
Re-order identity classes (factor ordering), according to position on the tree. This groups similar classes together which can be helpful, for example, when drawing violin plots.
Re-order identity classes according to position on the tree, assigning a numeric value ('1' is the leftmost node)
Show progress updates
A Seurat object where the cluster tree can be accessed with Tool
Note that the tree is calculated for an 'average' cell, so gene expression or PC scores are averaged across all cells in an identity class before the tree is constructed.
# NOT RUN {
pbmc_small
pbmc_small <- BuildClusterTree(object = pbmc_small)
Tool(object = pbmc_small, slot = 'BuildClusterTree')
# }
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