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#' Transpose an Assay (Data Frame)
#'
#' @description Transpose an object of class \code{data.frame} that contains
#' assay measurements while preserving row (feature) and column (sample)
#' names.
#'
#' @param assay_df A data frame with numeric values to transpose
#' @param omeNames Are the data feature names in the first column or in the row
#' names of \code{df}? Defaults to the first column. If the feature names
#' are in the row names, this function assumes that these names are accesible
#' by the \code{\link{rownames}} function called on \code{df}.
#' @param stringsAsFactors Should columns containing string information be
#' coerced to factors? Defaults to \code{FALSE}.
#'
#' @details This function is designed to transpose "tall" assay data frames
#' (where genes or proteins are the rows and patient or tumour samples are
#' the columns). This function also transposes the row (feature) names to
#' column names and the column (sample) names to row names. Notice that all
#' rows and columns (other than the feature name column, as applicable) are
#' numeric.
#'
#' Recall that data frames require that all elements of a single column to
#' have the same \code{\link{class}}. Therefore, sample IDs of a "tall" data
#' frame \strong{must} be stored as the column names rather than in the
#' first row.
#'
#' @return The transposition of \code{df}, with row and column names preserved
#' and reversed.
#'
#' @export
#'
#' @examples
#' x_mat <- matrix(rnorm(5000), ncol = 20, nrow = 250)
#' rownames(x_mat) <- paste0("gene_", 1:250)
#' colnames(x_mat) <- paste0("sample_", 1:20)
#' x_df <- as.data.frame(x_mat, row.names = rownames(x_mat))
#'
#' TransposeAssay(x_df, omeNames = "rowNames")
#'
TransposeAssay <- function(assay_df,
omeNames = c("firstCol", "rowNames"),
stringsAsFactors = FALSE){
omeNames <- match.arg(omeNames)
if(omeNames == "firstCol"){
featureNames_vec <- assay_df[, 1, drop = TRUE]
sampleNames_vec <- colnames(assay_df)[-1]
transpose_df <- as.data.frame(
t(assay_df[, -1]),
stringsAsFactors = stringsAsFactors
)
rownames(transpose_df) <- NULL
colnames(transpose_df) <- featureNames_vec
sampleNames_df <- data.frame(
Sample = sampleNames_vec,
stringsAsFactors = stringsAsFactors
)
transpose_df <- cbind(sampleNames_df, transpose_df)
} else {
featureNames_vec <- rownames(assay_df)
sampleNames_vec <- colnames(assay_df)
transpose_df <- as.data.frame(
t(assay_df),
stringsAsFactors = stringsAsFactors
)
colnames(transpose_df) <- featureNames_vec
rownames(transpose_df) <- sampleNames_vec
}
class(transpose_df) <- class(assay_df)
transpose_df
}
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