MethylMix_ModelGeneExpression: The MethylMix_ModelGeneExpression function

In MethylMix: MethylMix: Identifying methylation driven cancer genes

Description

Model gene expression as a function of gene expression with a simple linear regression model. Genes with a significant negative linear association between DNA methylation and gene expression are returned.

Usage

MethylMix_ModelGeneExpression(METcancer, GEcancer, CovariateData = NULL)

Arguments

METcancer	matrix with methylation data for cancer samples (genes in rows, samples in columns).
GEcancer	matrix with gene expression data for cancer samples (genes in rows, samples in columns).
CovariateData	vector (numeric or character) indicating a covariate to be included in the model to adjust for it. Not used in an standard run of MethylMix. It can be used if samples can from different tissue type, for example.

Value

vector with the names of the genes for which there is a significant linear and negative association between methylation and gene expression.

Examples

# load data sets
data(METcancer)
data(GEcancer)

# model gene expression
MethylMixResults <- MethylMix_ModelGeneExpression(METcancer, GEcancer)

MethylMix documentation built on Nov. 8, 2020, 11:08 p.m.