Calculate the network propagation score using a set of seed cells and cell-to-cell graph.
randomWalk_sparse(
intM,
queryCells,
gamma = 0.05,
seedWeight = "NO",
stationary_cutoff = 1e-05
)a sparse matrix indicating the adjacent matrix (m x m, where m is the cell number) of cell-to-cell network (M-kNN graph).
a logical vector indicating seed cells (TRUE) and non-seed cells (FALSE) with length of m, where m is the cell number. The length and position are corresponding to intM.
a numeric value indicating the probability of node restart at each step of random walk.
a numeric vector indicating the weight assigned to each node. "NO" (by default) means considering weights are equal (no weight).
Delta used for determine the stationary state between any two adjacent iterations.
a numeric vector of network propagation score with length of m, where m is the cell number.
mutualknn30 <- example_results$mutualknn30
seed_idx <- example_results$seed_idx
np_score <- randomWalk_sparse(intM = mutualknn30,
queryCells = rownames(mutualknn30)[seed_idx])
#> Stationary step: 95
#> Stationary Delta: 9.37125805585418e-06