R/data.R

In compbiomed/BatchQC: Batch Effects Quality Control Software

globalVariables(c("protein_sample_info", "protein_data", "batch_indicator",
    "signature_data", "bladder_meta", "bladder_data"))

#' Batch and Condition indicator for protein expression data
#'
#' This data consists of two batches and two conditions
#' corresponding to case and control for the protein expression data
#'
#' @name protein_sample_info
#' @docType data
#' @format A data frame with 24 rows and 2 variables:
#' \describe{
#'     \item{batch}{Batch Indicator}
#'     \item{category}{Condition (Case vs Control) Indicator}
#' }
#' @keywords datasets
#' @usage data(protein_sample_info)
"protein_sample_info"

#' Protein data with 39 protein expression levels
#'
#' This data consists of two batches and two conditions
#' corresponding to case and control. The columns are case/control
#' samples, and the rows represent 39 different proteins.
#'
#' @name protein_data
#' @docType data
#' @format A data frame with 39 rows and 24 variables
#' @keywords datasets
#' @usage data(protein_data)
"protein_data"


#' Batch and Condition indicator for signature data
#'
#' This dataset is from signature data captured when activating different growth
#' pathway genes in human mammary epithelial cells (GEO accession: GSE73628).
#' This data consists of three batches and ten different conditions
#' corresponding to control and nine different pathways.
#'
#' @name batch_indicator
#' @docType data
#' @format A data frame with 89 rows and 2 variables:
#' \describe{
#'     \item{batch}{batch}
#'     \item{condition}{condition}
#' }
#' @keywords datasets
#' @usage data(batch_indicator)
"batch_indicator"

#' Signature data with 1600 gene expression levels
#'
#' This data consists of three batches and ten conditions.
#' The columns are samples, and the rows represent
#' 1600 different genes.
#'
#' @name signature_data
#' @docType data
#' @format A data frame with 1600 rows and 89 variables
#' @keywords datasets
#' @usage data(signature_data)
"signature_data"

#' Bladder data upload
#' This function uploads the Bladder data set from the bladderbatch package.
#' This dataset is from bladder cancer data with 22,283 different microarray
#' gene expression data. It has 57 bladder samples with 3 metadata variables
#' (batch, outcome and cancer). It contains 5 batches, 3 cancer types (cancer,
#' biopsy, control), and 5 outcomes (Biopsy, mTCC, sTCC-CIS, sTCC+CIS, and
#' Normal). Batch 1 contains only cancer, 2 has cancer and controls, 3 has only
#' controls, 4 contains only biopsy, and 5 contains cancer and biopsy
#'
#' @usage bladder_data_upload()
#' @return a SE object with counts data and metadata
#'
#' @examples
#' library(bladderbatch)
#' se_object <- bladder_data_upload()
#'
#' @export
bladder_data_upload <- function() {
    if (!requireNamespace("bladderbatch")) {
        stop("You need to install the 'bladderbatch' package to use this
            data set.")
    }
    data(bladderdata, package = "bladderbatch", envir = environment())
    bladderEset <- bladderEset
    pheno <- pData(bladderEset) %>% select(-sample)
    edata <- exprs(bladderEset)
    se_object <- BatchQC::summarized_experiment(edata, pheno)

    return(se_object)
}