GeneNet: GeneNet

Description Usage Arguments Details Value Author(s) Examples

View source: R/GeneNet.R

Description

Generate correction and adjacency matrices for data and permutation

Usage

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GeneNet(data, labels, caseName, controlName, meanFilter = 0.2,
  SDFilter = 0.2, edgeCutoff = 0.004, permutationTimes = 10,
  CPUNumbers = 1, folder = "MetaDCN", pathwayDatabase, silent = FALSE)

Arguments

data

a list of matrices (studies) with rows as features and columns as samples.

labels

a list of vectors to specify the case/control labels for each subject corresponidng to the columns in each data matrix.

caseName

a character string denoting case label.

controlName

a character string denoting control label.

meanFilter

a number between 0 and 1. Features with mean below this cutoff will be filtered out.

SDFilter

a number between 0 and 1. Features with standard deviation (SD) will be filtered out.

edgeCutoff

a number between 0 and 1, denoting the proportion of edges to kept.

permutationTimes

a number to specify how many permutations to be used. Large number of permutations will be very time-consuming.

CPUNumbers

a number to specify how many CPUs are used for parallel, if multicores exists. Must be less than or equal to the permutationTimes.

folder

folder path to store results.

pathwayDatabase

a list with each element as a vector of pathway genes, and names as pathway names.

silent

TRUE/FALSE to specify if suppress screen output.

Details

This function will generate correction and adjacency matrices for data and permutations.

Value

GeneNet returns a list of information which will be used for SearchBM and MetaDCN function, and several RData files stored in folder path.

List of basic informations for SearchBM and MetaDCN input:

caseName

case names

controlName

control names

permutationTimes

permutation times

folder

folder path

pathwayDatabase

a list of pathways

CPUNumbers

CPU numbers from arguments

AdjacencyMatrices.RData is a list of adjacency matrices for case and control in each study in the order of case studies and control studies.

CorrelationMatrices.RData is a list of correlation matrices for case and control in each study.

AdjacencyMatricesPermutationP.RData is a list of correlation matrices for case and control in each study in permutation P.

Author(s)

Li Zhu (liz86@pitt.edu)

Examples

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data(pathwayDatabase)
data(example)
GeneNetRes <- GeneNet(data_2l, labels_2l, caseName="inv(16)", controlName="t(8;21)", meanFilter=0.8, SDFilter=0.8, edgeCutoff=0.1, permutationTimes=4, CPUNumbers=1, folder="MetaDCN", pathwayDatabase, silent=FALSE)
SearchBMRes <- SearchBM(GeneNetRes, MCSteps=500, jaccardCutoff=0.8, repeatTimes=3, outputFigure=TRUE, silent=FALSE)
MetaDNCRes <- MetaDCN(GeneNetRes, SearchBMRes, FDRCutoff=0.3, w1=NULL, silent=FALSE)

metaOmics/MetaDCN documentation built on May 29, 2019, 4:43 a.m.