cor_dnam_target_gene {MethReg} | R Documentation |
This function evaluate the correlation of the DNA methylation and target gene expression using spearman rank correlation test. Note that genes with RNA expression equal to 0 for all samples will not be evaluated.
cor_dnam_target_gene( pair.dnam.target, dnam, exp, filter.results = TRUE, min.cor.pval = 0.05, min.cor.estimate = 0, cores = 1 )
pair.dnam.target |
A dataframe with the following columns: regionID (DNA methylation) and target (target gene) |
dnam |
DNA methylation matrix or SummarizedExperiment object with regions/cpgs in rows and samples in columns are samples. Samples should be in the same order as gene expression matrix (exp). |
exp |
Gene expression matrix or SummarizedExperiment object (rows are genes, columns are samples) log2-normalized (log2(exp + 1)). Samples should be in the same order as the DNA methylation matrix. |
filter.results |
Filter results using min.cor.pval and min.cor.estimate thresholds |
min.cor.pval |
P-value threshold filter (default: 0.05) |
min.cor.estimate |
Correlation estimate threshold filter (default: not applied) |
cores |
Number of CPU cores to be used. Default 1. |
A data frame with the following information: regionID, target gene, correlation pvalue and estimate between DNA methylation and target gene expression, FDR corrected p-values.
dnam <- t(matrix(sort(c(runif(20))), ncol = 1)) rownames(dnam) <- c("chr3:203727581-203728580") colnames(dnam) <- paste0("Samples",1:20) exp <- dnam rownames(exp) <- c("ENSG00000232886") colnames(exp) <- paste0("Samples",1:20) pair.dnam.target <- data.frame( "regionID" = c("chr3:203727581-203728580"), "target" = "ENSG00000232886" ) # Correlated DNAm and gene expression, display only significant associations results.cor.pos <- cor_dnam_target_gene( pair.dnam.target = pair.dnam.target, dnam = dnam, exp = exp, filter.results = TRUE, min.cor.pval = 0.05, min.cor.estimate = 0.0 )