R/CpGsInfoAllRegions.R

In lissettegomez/coMethDMR: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies

#' Test associations of individual CpGs in multiple genomic regions with a continuous phenotype
#'
#' @param AllRegionNames_char vector of character strings with location info for all the genomic regions.
#' Each region should be specified in this format: "chrxx:xxxxxx-xxxxxx"
#' @param betas_df data frame of beta values for all genomic regions,
#' with row names = CpG IDs, column names = sample IDs
#' @param pheno_df a data frame with phenotype and covariate variables, with variable "Sample" for sample IDs.
#' @param contPheno_char character string of the continuous phenotype, to be tested against methylation values
#' @param covariates_char character vector of covariate variables names
#' @param arrayType Type of array, can be "450k" or "EPIC"
#'
#' @return a data frame with locations of the genomic region (Region), CpG ID (cpg), chromosome (chr),
#' position (pos), and results for testing association of methylation in individual CpGs with
#' continuous phenotype (slopeEstimate, slopePval), UCSC_RefGene_Name, UCSC_RefGene_Accession,
#' UCSC_RefGene_Group
#'
#' @export
#'
#' @examples
#'    data(betasChr22_df)
#'    data(pheno_df)
#'    AllRegionNames_char <- c("chr22:18267969-18268249", "chr22:18531243-18531447")
#'
#'    CpGsInfoAllRegions(
#'      AllRegionNames_char,
#'      betas_df = betasChr22_df,
#'      pheno_df, contPheno_char = "stage",
#'      covariates_char = c("age.brain", "sex")
#'    )
CpGsInfoAllRegions <- function(AllRegionNames_char, betas_df, pheno_df,
                               contPheno_char, covariates_char,
                               arrayType = c("450k","EPIC")){

  arrayType <- match.arg(arrayType)

  resultsAllRegions_ls <- lapply(
    AllRegionNames_char,
    FUN = CpGsInfoOneRegion,
    betas_df,
    pheno_df,
    contPheno_char,
    covariates_char,
    arrayType)

  resultsAllRegions_df <- do.call(rbind, resultsAllRegions_ls)

  unique(resultsAllRegions_df)

}