cor_tf_target_gene {MethReg} | R Documentation |
This function evaluate the correlation of a TF 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_tf_target_gene( pair.tf.target, exp, tf.activity.es, cores = 1, verbose = FALSE )
pair.tf.target |
A dataframe with the following columns: TF and target (target gene) |
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 tf.activity.es matrix |
tf.activity.es |
A matrix with normalized enrichment
scores for each TF across all samples to be used in linear models instead
of TF gene expression. See |
cores |
Number of CPU cores to be used. Default 1. |
verbose |
Show messages ? |
A data frame with the following information: TF, target gene, correlation p-value and estimate between TF and target gene expression, FDR corrected p-values.
exp <- t(matrix(sort(c(runif(40))), ncol = 2)) rownames(exp) <- c("ENSG00000232886","ENSG00000232889") colnames(exp) <- paste0("Samples",1:20) pair.tf.target <- data.frame( "TF" = "ENSG00000232889", "target" = "ENSG00000232886" ) # Correlated TF and gene expression results.cor.pos <- cor_tf_target_gene( pair.tf.target = pair.tf.target, exp = exp, ) # Correlated TF and gene expression results.cor.pos <- cor_tf_target_gene( pair.tf.target = pair.tf.target, exp = exp, tf.activity.es = exp )