smoothAndRecombine-matrix-method: Perform network smoothing on network when the network genes...

In netSmooth: Network smoothing for scRNAseq

Description

The gene network might be defined only on a subset of genes that are measured in any experiment. Further, an experiment might not measure all genes that are present in the network. This function projects the experiment data onto the gene space defined by the network prior to smoothing. Then, it projects the smoothed data back into the original dimansions.

Usage

## S4 method for signature 'matrix'
smoothAndRecombine(
  gene_expression,
  adj_matrix,
  alpha,
  smoothing.function = randomWalkBySolve,
  normalizeAdjMatrix = c("rows", "columns")
)

Arguments

gene_expression	gene expession data to be smoothed [N_genes x M_samples]
adj_matrix	adjacenty matrix of network to perform smoothing over. Will be column-normalized. Rownames and colnames should be genes.
alpha	network smoothing parameter (1 - restart probability in random walk model.
smoothing.function	must be a function that takes in data, adjacency matrix, and alpha. Will be used to perform the actual smoothing.
normalizeAdjMatrix	which dimension (rows or columns) should the adjacency matrix be normalized by. rows corresponds to in-degree, columns to out-degree.
filepath	String: Path to location where hdf5 output file is supposed to be saved. Will be ignored when regular matrices or SummarizedExperiment are used as input.

Value

matrix with network-smoothed gene expression data. Genes that are not present in smoothing network will retain original values.

netSmooth documentation built on Nov. 8, 2020, 5:33 p.m.