GEM_Emodel: GEM_Emodel Analysis

In fastGEM/GEM: GEM: fast association study for the interplay of Gene, Environment and Methylation

Description

GEM_Emodel is to find the association between methylation and environmental factor genome widely.

Usage

GEM_Emodel(env_file_name, covariate_file_name, methylation_file_name, Emodel_pv,
  output_file_name, qqplot_file_name, savePlot = TRUE)

Arguments

env_file_name	Text file with rows representing environment factor and columns representing samples, such as the example data file "env.txt".
covariate_file_name	Text file with rows representing covariate factors and columns representing samples, such as the example data file "cov.txt".
methylation_file_name	Text file with rows representing methylation profiles for CpGs, and columns representing samples, such as the example data file "methylation.txt".
Emodel_pv	The pvalue cut off. Associations with significances at Emodel_pv level or below are saved to output_file_name, with corresponding estimate of effect size (slope coefficient), test statistics and p-value. Default value is 1.0.
output_file_name	The result file with each row presenting a CpG and its association with environment, which contains CpGID, estimate of effect size (slope coefficient), test statistics, pvalue and FDR at each column.
qqplot_file_name	Image file name to present the QQ-plot for all p-value distribution.
savePlot	If save the plot.

Details

GEM_Emodel finds the association between methylation and environment genome-wide by performing matrix based iterative correlation and memory-efficient data analysis instead of millions of linear regressions (N = number_of_CpGs). The methylation data are the measurements for CpG probes, for example, 450,000 CpGs from Illumina Infinium HumanMethylation450 Array. The environmental factor can be a particular phenotype or environment factor from,for example, birth outcomes, maternal conditions or disease traits. The output of GEM_Emodel for particular environmental factor is a list of CpGs that are potential epigenetic biomarkers. GEM_Emodel runs linear regression like lm (M ~ E + covt), where M is a matrix with methylation data, E is a matrix with environment factor and covt is a matrix with covariates, and all read from the formatted text data file.

Value

save results automatically

Examples

DATADIR = system.file('extdata',package='GEM')
RESULTDIR = getwd()
env_file = paste(DATADIR, "env.txt", sep = .Platform$file.sep)
covariate_file = paste(DATADIR, "cov.txt", sep = .Platform$file.sep)
methylation_file = paste(DATADIR, "methylation.txt", sep = .Platform$file.sep)
Emodel_pv = 1
output_file = paste(RESULTDIR, "Result_Emodel.txt", sep = .Platform$file.sep)
qqplot_file = paste(RESULTDIR, "QQplot_Emodel.jpg", sep = .Platform$file.sep)
GEM_Emodel(env_file, covariate_file, methylation_file, Emodel_pv, output_file, qqplot_file)

fastGEM/GEM documentation built on Aug. 5, 2021, 7:33 p.m.