lm_meth: Linear regression GE~METH

In anna-pacinkova/intomics_package: Integrative analysis of multi-omics data to infer regulatory networks

Linear regression GE~METH

Description

lm_meth The linear regression model for a dependent variable GE and explanatory variable METH. Returns METH with significant coefficient, R^2 > threshold and R~Gaussian residuals.

Usage

lm_meth(ge_mat, meth_mat, gene, meth_probes, r_squared_thres, p_val_thres)

Arguments

ge_mat	matrix of gene expression with samples in rows and features in columns.
meth_mat	matrix of DNA methylaton with samples in rows and features in columns.
gene	character vector with given node name.
meth_probes	character vector methylation probes associated with a gene.
r_squared_thres	numeric vector to define the R^2 used as a threshold of significance in linear regression if lm_METH=TRUE (default=0.3).
p_val_thres	numeric vector to define the p-value used as a threshold of significance in linear regression if lm_METH=TRUE (default=0.05).

Value

Character vector with methylation probes

Examples

data(list=c("annot", "omics"), package="IntOMICS")
lm_meth(ge_mat = omics$ge, meth_mat = omics$meth, 
    gene = "ENTREZID:7482", meth_probes = annot[["ENTREZID:7482"]], 
    r_squared_thres = 0.3, p_val_thres = 0.05)

anna-pacinkova/intomics_package documentation built on Aug. 13, 2022, 11:38 a.m.