RepresentationMap: Generate multiple representations

In mkarikom/RSoptSC: Low-Rank Factorization for Subspace-clustering

Generate multiple representations

Description

Generate representations of the data to be used in lineage analysis.

Usage

RepresentationMap(
  flat_embedding = NULL,
  similarity_matrix,
  join_components = TRUE,
  normalize_S = TRUE,
  flat_embedding_method = "umap",
  ...
)

Arguments

flat_embedding	optionally provided low dim embedding, if not then 2d tsne will be used
similarity_matrix	the graphical embedding of the cells
join_components	boolean, whether or not to join disconnected components of the similarity matrix
normalize_S	whether or not to normalize the similarity matrix
flat_embedding_method	what method to use for flat embedding. Use umap by default. Can be umap or tsne.
...	arguments to called functions

Value

a list containing:

dist_flat	distance matrix on flat embedding
dist_graph	distance matrix on graph
adj_matrix	unweighted adjacency matrix
flat_embedding	the low dimensional embedding of the cells
similarity_graph	igraph object on the unweighted adjacency matrix
components	an igraph components object based on similarity_graph
n_components	number of components in components
sizes	sizes of components in components
members	list of members of components, sorted by component size and member index

mkarikom/RSoptSC documentation built on May 10, 2023, 1:10 a.m.