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# Constructor function for the scgps object of the SingleCellExperiment class
#'
#' new_scGPS_object
#'
#' \code{\link{new_scGPS_object}} generates a scGPS object in the
#' \linkS4class{SingleCellExperiment} class for use with the scGPS package. This
#' object contains an expression matrix, associated metadata (cells, genes,
#' clusters). The data are expected to be normalised counts.
#' @param ExpressionMatrix An expression matrix in data.frame or matrix format.
#' Rows should represent a transcript and its normalised counts,
#' while columns should represent individual cells.
#' @param GeneMetadata A data frame or vector containing gene identifiers used
#' in the expression matrix. The first column should hold the gene identifiers
#' you are using in the expression matrix. Other columns contain information
#' about the genes, such as their corresponding ENSEMBL transcript identifiers.
#' @param CellMetadata A data frame containing cell identifiers
#' (usually barcodes) and an integer representing which batch they belong to.
#' The column containing clustering information needs to be the first column in
#' the CellMetadata dataframe If clustering information is not available, users
#' can run CORE function and add the information to the scGPS before running
#' scGPS prediction
#' @return This function generates an scGPS object belonging to the
#' \linkS4class{SingleCellExperiment}.
#' @seealso \linkS4class{SingleCellExperiment}
#' @export
#' @examples
#' day2 <- day_2_cardio_cell_sample
#' t <-new_scGPS_object(ExpressionMatrix = day2$dat2_counts,
#' GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
#' colData(t); show(t); colnames(t)
#' @author Quan Nguyen, 2018-04-06
#'
#'
new_scGPS_object <- function(ExpressionMatrix = NULL, GeneMetadata = NULL,
CellMetadata = NULL) {
# Check that we have the essential arguments - an expression matrix
arg.check <- list(ExpressionMatrix = missing(ExpressionMatrix),
GeneMetadata = missing(GeneMetadata),
CellMetadata = missing(CellMetadata))
if (any(arg.check == TRUE)) {
missing.args <- names(which(arg.check == TRUE))
msg <- sprintf("Please supply the following arguments: %s\n",
as.character(unlist(missing.args)))
stop(msg)
}
if (!is.data.frame(ExpressionMatrix) &
!is.matrix(ExpressionMatrix)) {
stop(paste0("Please supply an expression matrix in one of the ",
"following formats: data.frame or matrix"))
}
# Create a new scGPS object.
scGPSset <- SingleCellExperiment(assays = list(counts = ExpressionMatrix),
rowData = GeneMetadata, colData = CellMetadata)
# All clear, return the object
return(scGPSset)
}
# Constructor function for the scgps object of the SummarizedExperiment class
#'
#' new_summarized_scGPS_object
#'
#' \code{\link{new_scGPS_object}} generates a scGPS object in the
#' \linkS4class{SingleCellExperiment} class for use with the scGPS package. This
#' object contains an expression matrix, associated metadata (cells, genes,
#' clusters). The data are expected to be normalised counts.
#' @param ExpressionMatrix An expression dataset in matrix format.
#' Rows should represent a transcript and its normalised counts,
#' while columns should represent individual cells.
#' @param GeneMetadata A data frame or vector containing gene identifiers used
#' in the expression matrix. The first column should hold the cell identifiers
#' you are using in the expression matrix. Other columns contain information
#' about the genes, such as their corresponding ENSEMBL transcript identifiers.
#' @param CellMetadata A data frame containing cell identifiers
#' (usually barcodes) and clustering information (the first column of the data
#' frame contains clustering information). The column containing clustering
#' information needs to be named as 'Cluster'. If clustering information is not
#' available, users can run CORE function and add the information to the scGPS
#' before running scGPS prediction
#' @return This function generates an scGPS object belonging to the
#' \linkS4class{SingleCellExperiment}.
#' @seealso \linkS4class{SingleCellExperiment}
#' @export
#' @examples
#' day2 <- day_2_cardio_cell_sample
#' t <-new_summarized_scGPS_object(ExpressionMatrix = day2$dat2_counts,
#' GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
#' colData(t); show(t); colnames(t)
#' @author Quan Nguyen, 2017-11-25
#'
#'
#'
new_summarized_scGPS_object <- function(ExpressionMatrix = NULL,
GeneMetadata = NULL, CellMetadata = NULL) {
# Check that we have the essential arguments - an expression matrix
arg.check <- list(ExpressionMatrix = missing(ExpressionMatrix),
GeneMetadata = missing(GeneMetadata),
CellMetadata = missing(CellMetadata))
if (any(arg.check == TRUE)) {
missing.args <- names(which(arg.check == TRUE))
msg <- sprintf("Please supply the following arguments: %s\n",
as.character(unlist(missing.args)))
stop(msg)
}
# Check data formats (to do: can add a series of checking here)
if (!is.matrix(ExpressionMatrix)) {
stop("Please supply an expression data in the matrix format")
}
# Create a new scGPS object.
scGPSset <- SummarizedExperiment(assays = list(ExpressionMatrix),
rowData = GeneMetadata, colData = CellMetadata)
# All clear, return the object
return(scGPSset)
}
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