R/eNames.R

In Krutik6/TimiRGeN: Time sensitive microRNA-mRNA integration, analysis and network generation tool

#' @title eNames
#' @description Extracts the gene IDs from nested dataframes created from the
#' addIds function.
#' @param MAE MultiAssayExperiment which will store output of eNames.
#' It is recommended to use the MAE which stores the output of addIds.
#' @param method Either 'c' or 's', respectively for combined or separated
#' analysis.
#' @param gene_IDs List of DE data and associated gene IDs. This is the
#' output from the addIds function, this should be found as metadata in
#' the MAE used in the addIds function.
#' @return A single list of entrez/ ensembl IDs for each time point. Output
#' will be stored as metadata in the input MAE.
#' @export
#' @importFrom stats complete.cases
#' @usage eNames(MAE, method = '', gene_IDs)
#' @examples
#'library(org.Mm.eg.db)
#'
#' miR <- mm_miR[1:50,]
#'
#' mRNA <- mm_mRNA[1:100,]
#'
#' Data <- startObject(miR = mm_miR, mRNA = mm_mRNA)
#'
#' Data <- getIdsMir(Data, assay(Data, 1), org.Mm.eg.db, 'mmu')
#'
#' Data <- getIdsMrna(Data, assay(Data, 2), mirror = 'useast', 'mmusculus', org.Mm.eg.db)
#'
#' Data <- combineGenes(MAE = Data, miR_data = assay(Data, 1),
#'                      mRNA_data = assay(Data, 2))
#'
#' Data <- genesList(MAE = Data, method = 'c', genetic_data = assay(Data, 9),
#'                   timeString = 'D')
#'
#' Data <- significantVals(MAE = Data, method = 'c',
#'                         geneList = metadata(Data)[[1]],
#'                         maxVal = 0.05, stringVal = "adjPVal")
#'
#' Data <- addIds(MAE = Data, method = "c",
#'               filtered_genelist = metadata(Data)[[2]],
#'               miR_IDs = assay(Data, 3), mRNA_IDs = assay(Data, 7))
#'
#' Data <- eNames(MAE = Data, method = "c", gene_IDs = metadata(Data)[[3]])
eNames <- function(MAE, method, gene_IDs){

    if (missing(MAE)) stop('MAE is missing. Add MultiAssayExperiment. The results of eNames will be stored in the MAE. Please use the addIds function first.')

    if (missing(method)) stop('method is missing. Please add method "c" for combined analysis or "s" for separated analysis.')

    if (missing(gene_IDs)) stop('gene_IDs is missing. Add a list of nested dataframes with entrezID/ ensembl gene name information. Please use the addIDs function first. Output of the addIds function will be stored as metadata of the MAE used in the addIds function.')

    metadata <- `metadata<-` <- NULL

    # If c is choses
    if (method == 'c') {

      ID_Column <- ncol(gene_IDs[[1]])

        # Retreive all the string from the ID_Column from each list
        e <- lapply(gene_IDs, function(x){x[[ID_Column]]})

        ID_list <- lapply(e, function(x){ x[stats::complete.cases(x)]})

        # store into MAE object
        metadata(MAE)[["ID_list"]] <- ID_list

    return(MAE)

    } else if (method == 's') {

      ID_Column <- ncol(gene_IDs[[1]][[1]])

        # Retrieve all the string from the ID_Column from each list within
        # a list
        Y <- sapply(gene_IDs, function(x){sapply(x, `[[`, ID_Column)})

        X <- vapply(gene_IDs, function(x){list(names(x))}, FUN.VALUE = list(1))

        Xnames <- unlist(X)

        names(Y) <- Xnames

        ID_list <- lapply(Y, function(x){ x[stats::complete.cases(x)]})

        # store into MAE object
        metadata(MAE)[["ID_list"]] <- ID_list

    return(MAE)

    } else print('Enter c or s as method.')
}