find_extreme_cells: Identify candidate start cells for the trajectory

In SLICER: Selective Locally Linear Inference of Cellular Expression Relationships

Description

Plots the embedding generated by LLE and highlights potential starting cells for the trajectory. The candidates are chosen based on the longest shortest path through the nearest neighbor graph.

Usage

find_extreme_cells(traj_graph, embedding)

Arguments

traj_graph	Nearest neighbor graph built from LLE embedding
embedding	Low-dimensional LLE embedding of cells

Value

Indices of potential starting cells

Examples

genes=1:200
cells=sample(1:500,30)
k=10
traj_lle = lle::lle(traj[cells,genes],m=2,k)$Y
traj_graph = conn_knn_graph(traj_lle,5)
find_extreme_cells(traj_graph,traj_lle)

Example output

finding neighbours
calculating weights
computing coordinates
[1] 22 30

SLICER documentation built on May 1, 2019, 6:32 p.m.