CpGsInfoAllRegions: Test Associations Between Regions and Phenotype

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

Test Associations Between Regions and Phenotype

Description

Test associations of individual CpGs in multiple genomic regions with a continuous phenotype

Usage

CpGsInfoAllRegions(
  AllRegionNames_char,
  allRegions_gr = NULL,
  betas_df,
  pheno_df,
  contPheno_char,
  covariates_char,
  genome = c("hg19", "hg38"),
  arrayType = c("450k", "EPIC")
)

Arguments

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"
allRegions_gr	An object of class GRanges with location information for the regions. If this argument is NULL, then the regions in AllRegionNames_char are used. If this argument is not NULL, then region_gr will overwrite any supplied ranges in AllRegionNames_char.
betas_df	data frame of beta values for all genomic regions, with row names = CpG IDs amd column names = sample IDs
pheno_df	a data frame with phenotype and covariate variables, with variable "Sample" for sample IDs.
contPheno_char	character string of the continuous phenotype to be tested against methylation values
covariates_char	character vector of covariate variables names
genome	human genome of reference hg19 (default) or hg38
arrayType	Type of array, can be "450k" or "EPIC"

Value

a data frame with locations of the genomic region (Region), CpG ID (cpg), chromosome (chr), position (pos), results for testing association of methylation in individual CpGs with the continuous phenotype (slopeEstimate, slopePval), UCSC_RefGene_Name, UCSC_RefGene_Accession, and UCSC_RefGene_Group

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 = pheno_df,
     contPheno_char = "stage",
     covariates_char = c("age.brain", "sex")
   )
   

TransBioInfoLab/coMethDMR documentation built on Sept. 14, 2022, 7:09 p.m.