visualise.clusters: Visualize clusters of genes using heatmap and consensus...

In hms-dbmi/crestree: Analysis of branching branching trajectories from single-cell data

Description

Visualize clusters of genes using heatmap and consensus tree-projected pattern.

Usage

visualise.clusters(r, emb, clust = NA, clust.n = 5, n.best = 4,
  best.method = "cor", cex.gene = 1, cex.cell = 0.1, cex.tree = 2,
  subtree = NA, reclust = TRUE)

Arguments

r	pptree object
emb	cells embedding
clust	a vector of cluster numbers named by genes
n.best	show n.best the most representative genes on the heatmap for each cluster
best.method	use method to select the most representative genes. Current options: "pca" selects genes with the highest loading on pc1 component reconstructed using genes from a cluster, "cor" selects genes that have the highest average correlation with other genes from a cluster.
cex.gene	size of gene names
cex.cell	size of cells on embedding
cex.tree	width of line of tree on embedding
subtree	visualize clusters for a given subtree
reclust	whether to reorder cells inside individual clusters on heatmap according to hierarchical clustering using Ward linkage and 1-Pearson as a distance between genes. By default is FALSE.

hms-dbmi/crestree documentation built on July 11, 2019, 8:04 p.m.