plotClusterFactors: Plot heatmap of cluster/factor correspondence

In rliger: Linked Inference of Genomic Experimental Relationships

Plot heatmap of cluster/factor correspondence

Description

Generates matrix of cluster/factor correspondence, using sum of row-normalized factor loadings for every cell in each cluster. Plots heatmap of matrix, with red representing high total loadings for a factor, black low. Optionally can also include dendrograms and sorting for factors and clusters.

Usage

plotClusterFactors(
  object,
  use.aligned = FALSE,
  Rowv = NA,
  Colv = "Rowv",
  col = NULL,
  return.data = FALSE,
  ...
)

Arguments

object	liger object.
use.aligned	Use quantile normalized factor loadings to generate matrix (default FALSE).
Rowv	Determines if and how the row dendrogram should be computed and reordered. Either a dendrogram or a vector of values used to reorder the row dendrogram or NA to suppress any row dendrogram (and reordering) (default NA for no dendrogram).
Colv	Determines if and how the column dendrogram should be reordered. Has the same options as the Rowv argument (default 'Rowv' to match Rowv).
col	Color map to use (defaults to red and black)
return.data	Return matrix of total factor loadings for each cluster (default FALSE).
...	Additional parameters to pass on to heatmap()

Value

If requested, matrix of size num_cluster x num_factor

Examples

ligerex <- createLiger(list(ctrl = ctrl, stim = stim))
ligerex <- normalize(ligerex)
ligerex <- selectGenes(ligerex)
ligerex <- scaleNotCenter(ligerex)
ligerex <- optimizeALS(ligerex, k = 5, max.iter = 2)
ligerex <- quantile_norm(ligerex)
ligerex <- louvainCluster(ligerex)
plotClusterFactors(ligerex)

rliger documentation built on Nov. 9, 2023, 1:07 a.m.