R/GDS2MA.R

In seandavi/GEOquery: Get data from NCBI Gene Expression Omnibus (GEO)

#' @importClassesFrom limma MAList
#' @export
"GDS2MA" <- function(GDS, do.log2 = FALSE, GPL = NULL, AnnotGPL = TRUE, getGPL = TRUE) {
    if (!is.null(GPL) & getGPL) {
        GPL <- getGEO(Meta(GDS)$platform, AnnotGPL = AnnotGPL)
        ord.table <- match(Table(GDS)[, 1], Table(GPL)[, 1])
        # exclude non-numeric columns
    }
    inc.columns <- grep("GSM", colnames(Table(GDS)))
    mat <- suppressWarnings(as.matrix(apply(Table(GDS)[, inc.columns], 2, function(x) {
        as.numeric(as.character(x))
    })))
    if (do.log2) {
        M <- log2(mat)
    } else {
        M <- mat
    }
    if (is.null(GPL)) {
        ## No GPL requested
        return(new("MAList", list(M = M, A = NULL, targets = Columns(GDS), notes = Meta(GDS))))
    } else {
        ## include GPL
        return(new("MAList", list(M = M, A = NULL, targets = Columns(GDS), genes = Table(GPL)[ord.table,
            ], notes = Meta(GDS))))
    }

    return(MA)
}

#' @importClassesFrom Biobase ExpressionSet
#' @export
"GDS2eSet" <- function(GDS, do.log2 = FALSE, GPL = NULL, AnnotGPL = TRUE, getGPL = TRUE) {
    # exclude non-numeric columns
    inc.columns <- grep("GSM", colnames(Table(GDS)))
    mat <- suppressWarnings(as.matrix(apply(Table(GDS)[, inc.columns], 2, function(x) {
        as.numeric(as.character(x))
    })))
    if (do.log2) {
        expr <- log2(mat)
    } else {
        expr <- mat
    }
    rownames(expr) <- as.character(Table(GDS)$ID_REF)
    tmp <- Columns(GDS)
    rownames(tmp) <- as.character(tmp$sample)
    pheno <- new("AnnotatedDataFrame", data = tmp)
    mabstract = ifelse(is.null(Meta(GDS)$description), "", Meta(GDS)$description)
    mpubmedids = ifelse(is.null(Meta(GDS)$pubmed_id), "", Meta(GDS)$pubmed_id)
    mtitle = ifelse(is.null(Meta(GDS)$title), "", Meta(GDS)$title)
    featuredata = new("AnnotatedDataFrame", data = data.frame(row.names = rownames(expr)))
    if (getGPL | !is.null(GPL)) {
        if (is.null(GPL)) {
            GPL <- getGEO(Meta(GDS)$platform, AnnotGPL = AnnotGPL)
        }
        ord.table <- match(Table(GDS)[, 1], Table(GPL)[, 1])
        dt <- Table(GPL)
        rownames(dt) <- as.character(dt$ID)
        vardt = data.frame(Column = Columns(GPL)[, 1], labelDescription = Columns(GPL)[,
            2])
        ## GEO started using the same column names for both GO IDs and textual
        ## descriptions, so had to be made unique.
        vardt[, 1] <- make.unique(as.character(vardt[, 1]))
        rownames(vardt) = vardt[, 1]
        colnames(dt) <- rownames(vardt)
        featuredata <- new("AnnotatedDataFrame", data = dt[ord.table, ], varMetadata = vardt)
    }
    eset <- new("ExpressionSet", exprs = expr, phenoData = pheno, featureData = featuredata,
        experimentData = new("MIAME", abstract = mabstract, title = mtitle, pubMedIds = mpubmedids,
            other = Meta(GDS)))
    return(eset)
}