R/read.expr.R

In metaOmics/preproc: Preprocessing of Normalized Gene Expression Data

#' Import gene expression data set into R and reformat it to the form
#' required for other functions in this package.
#'
#' The file to be read should be prepared strictly according
#' following format. The first column should be gene ID and the
#' remaining columns should be the gene expressions for samples. The
#' first row should be sample names and the remaining rows
#' should be gene expression profiles for the samples.
#' @title Import and reformat gene expression data set
#' @param file.name a character string of the name of the file to be
#' read. See details.
#' @param name The name of the Study object returned
#' @param dtype The data type of the dataset (should be one of DTYPE.all)
#' @param clinical.file if there is a clinical file containing clinical
#' data relevent to the dataset.
#' @param log logical. Specify whether the gene expressions need to
#' be log2-transformed. The default is \code{TRUE}.
#' @param sep the field separator character. Values on each line of
#' the file are separated by this character. If \code{sep = ""}, the
#' separator is 'white space', that is one or more spaces, tabs,
#' newlines or carriage returns. The default is \code{,}. See
#' \link{read.csv}.
#' @param quote the set of quoting characters. To disable quoting
#' altogether, use \code{quote = ""}.  See \link{scan} for the
#' behaviour on quotes embedded in quotes. Quoting is only
#' considered for columns read as character, which is all of them
#' unless colClasses is specified.  The default is \code{\"}. See
#' \link{read.csv}.
#' @param header a logical value indicating whether the file contains
#' the names of the variables as its first line. If missing, the
#' value is determined from the file format: \code{header} is set to
#' \code{TRUE} if and only if the first row contains one fewer field
#' than the number of columns. The default is \code{TRUE}. See
#' \link{read.csv}.
#' @return A Study object
#' @author Lin Wang, Schwannden Kuo
#' @importFrom utils read.csv
#' @export
#' @examples
#' data(study.eg)
#' data(preproc.option)
#' write.csv(study.eg@datasets[[1]], file="expr.csv")
#' write.csv(study.eg@clinicals[[1]], file="clinical.csv")
#' # Simply read expression data and append clinical data later
#' study <- ReadExpr(file.name="expr.csv", name="test", dtype=DTYPE.microarray)
#' clinical <- ReadClinical(file.name="clinical.csv")
#' study <- setClinical(study, list(clinical))
#' # Read expression and clinical data
#' study <- ReadExpr(file.name="expr.csv", name="test", dtype=DTYPE.microarray,
#'                    clinical.file="clinical.csv")
ReadExpr <- function(file.name, name, dtype, clinical.file=NULL,
                     log=TRUE, sep=',', quote='"', header=T) {
  res <- read.csv(file.name, sep=sep, quote=quote, header=header, row.names=1)
  expr <- as.matrix(res)
  if (log) {
    expr[expr <= 0] <- 0.001
    expr <- log2(expr)
  }

  clinicals <- list()
  if (!is.null(clinical.file)) {
    clinical <- ReadClinical(clinical.file, sep=sep, quote=quote)
    clinicals <- list(clinical)
  }

  study <- new("Study",
    name=name,
    dtype=dtype,
    datasets=list(expr),
    clinicals=clinicals
  )
  return(study)
}

#' Title Read Clinical File
#'
#' @param file.name path to clinical file
#' @param sep the field separator character. Values on each line of
#' the file are separated by this character. If \code{sep = ""}, the
#' separator is 'white space', that is one or more spaces, tabs,
#' newlines or carriage returns. The default is \code{,}. See
#' \link{read.csv}.
#' @param quote the set of quoting characters. To disable quoting
#' altogether, use \code{quote = ""}.  See \link{scan} for the
#' behaviour on quotes embedded in quotes. Quoting is only
#' considered for columns read as character, which is all of them
#' unless colClasses is specified.  The default is \code{\"}. See
#' \link{read.csv}.
#'
#' @return a data.frame of clinical data
#' @export
#'
#' @examples
#' data(study.eg)
#' data(preproc.option)
#' write.csv(study.eg@datasets[[1]], file="expr.csv")
#' write.csv(study.eg@clinicals[[1]], file="clinical.csv")
#' study <- ReadExpr(file.name="expr.csv", name="test", dtype=DTYPE.microarray)
#' clinical <- ReadClinical(file.name="clinical.csv")
#' study <- setClinical(study, list(clinical))
ReadClinical <- function(file.name, sep=",", quote='"') {
  read.csv(file.name, sep=sep, quote=quote, header=T, row.names=1)
}