R/prepareChi.r

In huerqiang/GeoTcgaData: Processing Various Types of Data on GEO and TCGA

#' Preparer file for chi-square test
#'
#' @param cnv result of ann_merge()
#'
#' @return a matrix
#' @export
#'
#' @examples
#' cnv <- matrix(c(
#'     -1.09150, -1.47120, -0.87050, -0.50880,
#'     -0.50880, 2.0, 2.0, 2.0, 2.0, 2.0, 2.601962, 2.621332, 2.621332,
#'     2.621332, 2.621332, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0,
#'     2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0
#' ), nrow = 5)
#' cnv <- as.data.frame(cnv)
#' rownames(cnv) <- c("AJAP1", "FHAD1", "CLCNKB", "CROCCP2", "AL137798.3")
#' colnames(cnv) <- c(
#'     "TCGA-DD-A4NS-10A-01D-A30U-01", "TCGA-ED-A82E-01A-11D-A34Y-01",
#'     "TCGA-WQ-A9G7-01A-11D-A36W-01", "TCGA-DD-AADN-01A-11D-A40Q-01",
#'     "TCGA-ZS-A9CD-10A-01D-A36Z-01", "TCGA-DD-A1EB-11A-11D-A12Y-01"
#' )
#' cnv_chi_file <- prepare_chi(cnv)
prepare_chi <- function(cnv) {
    file1 <- cnv
    sampless <- rep(0, ncol(file1))
    for (i in seq_len(length(sampless)))
    {
        a <- unlist(strsplit(colnames(file1)[i], "-"))[4]
        sampless[i] <- substring(a, 1, 1)
    }

    cnv_chi <- matrix(0, nrow(cnv), 4)
    rownames(cnv_chi) <- rownames(cnv)
    colnames(cnv_chi) <- c("normalCNV", "normalWild", "tumorCNV", "tumorWild")
    for (i in seq_len(nrow(file1)))
    {
        normalCNV <- 0
        normalWild <- 0
        tumorCNV <- 0
        tumorWild <- 0
        for (j in seq_len(ncol(file1)))
        {
            if ((sampless[j] == "1") &&
                (abs(as.numeric(file1[i, j]) - 2) > 0.5)) {
                normalCNV <- normalCNV + 1
            }
            if ((sampless[j] == "1") &&
                (abs(as.numeric(file1[i, j]) - 2) <= 0.5)) {
                normalWild <- normalWild + 1
            }
            if ((sampless[j] == "0") &&
                (abs(as.numeric(file1[i, j]) - 2) > 0.5)) {
                tumorCNV <- tumorCNV + 1
            }
            if ((sampless[j] == "0") &&
                (abs(as.numeric(file1[i, j]) - 2) <= 0.5)) {
                tumorWild <- tumorWild + 1
            }
        }
        cnv_chi[i, ] <- c(normalCNV, normalWild, tumorCNV, tumorWild)
    }
    return(cnv_chi)
}