compute_similarity: Compute similarity based on trajectory

In trang1618/tdapseudotime: Temporal Phenotyping via Topological Data Analysis and Pseudo Time

Description

Compute similarity based on trajectory

Usage

compute_similarity(
  processed_data,
  node_color,
  trajectories,
  f_sim_map = NULL,
  verbose = TRUE
)

Arguments

processed_data	Dataframe. Processed from original data.
node_color	Dataframe mapping node to cluster and corresponding color.
trajectories	List of trajectories computed from shortest paths.
f_sim_map	TDAmapper object
verbose	Boolean. Whether to print trajectory.

Value

List of two components: dataframe with various similarity measures and dataframe of the observations mapped to corresponding node and cluster.

Examples

my_tda <- map_tda(scaled_lab_mat)
my_graph <- make_tda_graph(my_tda, processed_data, 'time')
my_trajs <- find_trajectories(processed_data, my_tda, my_graph)
compute_similarity(processed_data, my_graph$node_color, my_trajs, my_tda)

trang1618/tdapseudotime documentation built on Feb. 9, 2021, 6:14 p.m.