# Assessing the regulatory potential of DNA methylation regions or sites on gene transcription

## Documentation for package ‘MethReg’ version 1.19.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

clinical | TCGA-COAD clinical matrix for 38 samples retrieved from GDC using TCGAbiolinks
cor_dnam_target_gene | Evaluate correlation of DNA methylation region and target gene expression
cor_tf_target_gene | Evaluate correlation of TF expression and target gene expression
create_triplet_distance_based | Map DNAm to target genes using distance approaches, and TF to the DNAm region using JASPAR2024 TFBS.
create_triplet_regulon_based | Map TF and target genes using regulon databases or any user provided target-tf. Maps TF to the DNAm region with TFBS using JASPAR2020 TFBS.
dna.met.chr21 | TCGA-COAD DNA methylation matrix (beta-values) for 38 samples (only chr21) retrieved from GDC using TCGAbiolinks
export_results_to_table | Format MethReg results table and export to XLSX file
filter_dnam_by_quant_diff | Select regions with variations in DNA methylation levels above a threshold
filter_exp_by_quant_mean_FC | Select genes with variations above a threshold
filter_genes_zero_expression | Remove genes with gene expression level equal to 0 in a substantial percentage of the samples
gene.exp.chr21.log2 | TCGA-COAD gene expression matrix (log2 (FPKM-UQ + 1)) for 38 samples (only chromosome 21) retrieved from GDC using TCGAbiolinks
get_human_tfs | Access human TF from Lambert et al 2018
get_met_probes_info | Get HM450/EPIC manifest files from Sesame package
get_promoter_avg | Summarize promoter DNA methylation beta values by mean.
get_region_target_gene | Obtain target genes of input regions based on distance
get_residuals | Get residuals from regression model
get_tf_ES | Calculate enrichment scores for each TF across all samples using dorothea and viper.
get_tf_in_region | Get human TFs for regions by either scanning it with motifmatchr using JASPAR 2024 database or overlapping with TF chip-seq from user input
interaction_model | Fits linear models with interaction to triplet data (Target, TF, DNAm), where DNAm is a binary variable (samples in Q1 or Q4)
make_dnam_se | Transform DNA methylation array into a summarized Experiment object
make_exp_se | Transform gene expression matrix into a Summarized Experiment object
make_granges_from_names | Create a Granges object from a genmic region string
make_names_from_granges | Create region name from Granges
methReg_analysis | Wrapper for MethReg functions
plot_interaction_model | Plot interaction model results
plot_stratified_model | Plot stratified model results
readRemap2022 | Access REMAP2022 non-redundant peaks
stratified_model | Fits linear models to triplet data (Target, TF, DNAm) for samples with high DNAm or low DNAm separately, and annotates TF (activator/repressor) and DNam effect over TF activity (attenuate, enhance).