R/Methods.R

In mulea: Enrichment Analysis using Multiple Ontologies and False Discovery Rate

checkIfPoolIncludeSample <- function(model, sampleVector, poolVector = NULL) {
    # Chcking if experiment data all in model data.
    if (0 != length(poolVector)) {
        if (0 != sum(!(sampleVector %in% poolVector))) {
            to_msg <- paste(setdiff(sampleVector, unique(poolVector)), 
                collapse = ", ")
                warning("element_names are outside of pool.", " ", to_msg)
            return(setdiff(sampleVector, setdiff(sampleVector, 
                unique(poolVector))))}
        } else { if (0 != sum(!(sampleVector %in% unique(unlist(
            model$list_of_values))))) {
            to_msg <- paste(setdiff(sampleVector, unique(
                unlist(model$list_of_values))), collapse = ", ")
                warning("element_names are outside of gmt.", " ", to_msg)
                return(setdiff(sampleVector, setdiff(sampleVector, unique(
                    unlist(model$list_of_values)))))}}
    return(sampleVector)
}

cutGmtToPool <- function(gmt, pool) {cutDF <- plyr::ddply(.data = gmt,
    .variables = c("ontology_id"),
    .fun = function(dfRow) { dfRow$list_of_values[[1]] <- intersect(
        dfRow$list_of_values[[1]], pool)
        dfRow })
    cutDF
}