randomWalk_sparse: randomWalk_sparse

In fl-yu/SCAVENGE: Identifying genetic trait/phenotype relevant cell type/state at single cell resolution

randomWalk_sparse

Description

Calculate the network propagation score using a set of seed cells and cell-to-cell graph

Usage

randomWalk_sparse(
  intM,
  queryCells,
  gamma = 0.05,
  seedWeight = "NO",
  stationary_cutoff = 1e-05
)

Arguments

intM	a sparse matrix indicating the adjacent matrix (m x m, where m is the cell number) of cell-to-cell network (M-kNN graph)
queryCells	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
gamma	a numeric value indicating the probability of node restart at each step of random walk
seedWeight	a numeric vector indicating the weight assigned to each node. "NO" (by default) means considering weights are equal (no weight)
stationary_cutoff	delta used for determine the stationary state between any two adjacent iterations

Value

a numeric vector of network propagation score with length of m, where m is the cell number

Examples

## Not run: 
randomWalk_sparse <- tfidf(intM, queryCells, gamma=0.05, seedWeight="NO", stationary_cutoff=1e-5)
## End(Not run)

fl-yu/SCAVENGE documentation built on April 2, 2022, 10:56 a.m.