nearestNeighborConnectivity: Connectivity to a constant number of nearest neighbors

Description

Given expression data and basic network parameters, the function calculates connectivity of each gene to a given number of nearest neighbors.

Usage

nearestNeighborConnectivity(datExpr, 
         nNeighbors = 50, power = 6, type = "unsigned", 
         corFnc = "cor", corOptions = "use = 'p'", 
         blockSize = 1000,
         sampleLinks = NULL, nLinks = 5000, setSeed = 38457,
         verbose = 1, indent = 0)

Value

A vector with one component for each gene containing the nearest neighbor connectivity.

Arguments

datExpr: a data frame containing expression data, with rows corresponding to samples and columns to genes. Missing values are allowed and will be ignored.
nNeighbors: number of nearest neighbors to use.
power: soft thresholding power for network construction. Should be a number greater than 1.
type: a character string encoding network type. Recognized values are (unique abbreviations of) "unsigned", "signed", and "signed hybrid".
corFnc: character string containing the name of the function to calculate correlation. Suggested functions include "cor" and "bicor".
corOptions: further argument to the correlation function.
blockSize: correlation calculations will be split into square blocks of this size, to prevent running out of memory for large gene sets.
sampleLinks: logical: should network connections be sampled (TRUE) or should all connections be used systematically (FALSE)?
nLinks: number of links to be sampled. Should be set such that nLinks * nNeighbors be several times larger than the number of genes.
setSeed: seed to be used for sampling, for repeatability. If a seed already exists, it is saved before the sampling starts and restored upon exit.
verbose: integer controlling the level of verbosity. 0 means silent.
indent: integer controlling indentation of output. Each unit above 0 adds two spaces.

Author

Peter Langfelder

Details