smoothAndRecombine,matrix-method {netSmooth} | R Documentation

## Perform network smoothing on network when the network genes and the experiment genes aren't exactly the same.

### 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.
`chunk.size` | integer in [1,length(colnames[x])]. Number of columns that processed at the same time when using disk based DelayedMatrix. Will be ignored when regular matrices or SummarizedExperiment are used as input.
`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.

[Package netSmooth version 1.6.0 Index]