View source: R/cor_dnam_target_gene.R
cor_dnam_target_gene | 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
)
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