View source: R/randomWalk_sparse.R

randomWalk_sparse | R Documentation |

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 )

`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 |

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

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

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