combiningMappings {STATegRa} | R Documentation |
This function combines several annotation so that measurements across different datasets are mapped to the same reference elements (e.g., genes). The annotations should all be either data frame / matrices, named vectors/lists, or bioMap objects. See the examples for further details
combiningMappings(mappings, reference = NULL, retainAll = FALSE)
mappings |
List of annotations. |
reference |
If the annotations are data frame, matrices or bioMap objects, the name of the column containing the reference elements |
retainAll |
Logical, if set to TRUE measurements that have no counterparts in other datasets are retained |
A data frame encoding the mapping across several dataset
Vincenzo Lagani
Nestoras Karathanasis, Ioannis Tsamardinos and Vincenzo Lagani. omicsNPC: applying the Non-Parametric Combination methodology to the integrative analysis of heterogeneous omics data. Submitted to PlosONE.
#Example 1 #Mapping with data frames mRNA <- data.frame(gene = rep(c('G1', 'G2', 'G3'), each = 2), probeset = paste('p', 1:6, sep = '')); methylation <- data.frame(gene = c(rep('G1', 3), rep('G2', 4)), methy = paste('methy', 1:7, sep = '')); miRNA <- data.frame(gene = c(rep('G1', 2), rep('G2', 1), rep('G3', 2)), miR = c('miR1', 'miR2', 'miR1', 'miR1', 'miR2')); mappings <- list(mRNA = mRNA, methylation = methylation, miRNA = miRNA); combiningMappings(mappings = mappings, retainAll = TRUE) #Example 2 #Mapping with character vectors mRNA <- rep(c('G1', 'G2', 'G3'), each = 2); names(mRNA) = paste('p', 1:6, sep = ''); methylation <- c(rep('G1', 3), rep('G2', 4)); names(methylation) = paste('methy', 1:7, sep = ''); miRNA <- c(rep('G1', 2), rep('G2', 1), rep('G3', 2)); names(miRNA) = c('miR1', 'miR2', 'miR1', 'miR1', 'miR2'); mappings <- list(mRNA = mRNA, methylation = methylation, miRNA = miRNA); combiningMappings(mappings = mappings, retainAll = TRUE)