Description Usage Arguments Details Value Examples
View source: R/CpGsInfoOneRegion.R
Test associations of individual CpGs in a genomic region with a continuous phenotype
1 2 3 4 5 6 7 8 | CpGsInfoOneRegion(
regionName_char,
betas_df,
pheno_df,
contPheno_char,
covariates_char,
arrayType = c("450k", "EPIC")
)
|
regionName_char |
character string of location information for a genomic region, specified in the format of "chrxx:xxxxxx-xxxxxx" |
betas_df |
data frame of beta values with row names = CpG IDs, 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 |
arrayType |
Type of array, can be "450k" or "EPIC" |
This function implements linear models that test association between methylation values in a genomic region with a continuous phenotype. Note that methylation M values are used as regression outcomes in these models. The model for each CpG is:
methylation M value ~ contPheno_char + covariates_char
a data frame with location of the genomic region (Region), CpG ID (cpg), chromosome (chr), position (pos), results for testing association of methylation in individual CpGs with continuous phenotype (slopeEstimate, slopePval) and annotations for the regions
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data(betasChr22_df)
data(pheno_df)
CpGsInfoOneRegion(
regionName_char = "chr22:19709548-19709755",
betas_df = betasChr22_df,
pheno_df, contPheno_char = "stage",
covariates_char = c("age.brain", "sex"),
arrayType = "450k"
)
# not adjusting for covariates
CpGsInfoOneRegion(
regionName_char = "chr22:18267969-18268249",
betas_df = betasChr22_df,
pheno_df, contPheno_char = "stage",
covariates_char = NULL
)
|
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