R/binary.cnr.R

In SingerLab/gac: Genetic Analysis of Cells

#' build binary CNR from integer copy number data
#'
#' This function builds a binary, incidence, matrix from the cnr$X.  It was designed as a helper function to generate the input for infSCITE.
#'
#' Because infSCITE was developed for mutation data, this function creates a precense/absence matrix of the data
#' 
#' By default, anything not diploid is 1.
#'
#' @param cnr a copy number matrix to convert to an incidence matrix
#' 
#' @param base.ploidy expected cell ploidy, e.g. 2N = 2, 4N = 4.
#' 
#' @return
#'
#' Returns an incidence matrix for X as part of the cnr object
#'
#' \itemize{
#'   \item Z incidence matrix from X, copy number != 2 is 1, all 2 are 0
#' }
#' 
#' @examples
#'
#' data(cnr)
#'
#' Z <- binary.cnr(cnr)
#'  
#' @export
binary.cnr <- function(cnr, base.ploidy = 2) {
    
    Z <- binary.X(cnr[["X"]], bulk = cnr$bulk,
                  base.ploidy = base.ploidy)
    
    cnr[["Z"]] <- Z
    
    return(cnr)
    
} ## binary.cnr



#' build binary matrix from integer copy number data
#'
#' This function builds a binary alteration incidence matrix from copy number data.
#' Anything not equal to base.ploidy is 1.
#'
#' @param X a copy number matrix to convert to an incidence matrix
#'
#' @param bulk logical, if TRUE data is bulk DNA is cbioportal calls, default is FALSE for integer copy number
#'
#' @param base.ploidy expected ploidy, e.g. 2N = 2, 4N = 4
#'
#' @return
#'
#' Returns an incidence matrix for X, when X != base.ploidy
#' 
#' @examples
#'
#' data(cnr)
#'
#' Z <- binary.X(cnr$X, bulk = cnr$bulk)
#' 
#' Z <- binary.X(cnr$genes[, c("CDK4", "MDM2")], bulk = cnr$bulk)
#' 
#' @export
binary.X <- function(X, bulk, base.ploidy = 2) {

    if(bulk) {
        ## check its cbioportal notation
        assertthat::assert_that(any(c("-2", "-1") %in% names(table(X))))
        base.ploidy <- 0
    }
    
    Z <- apply(X != base.ploidy, 2, as.numeric)
    
    return(Z)

} ## binary.X



#' binaryDDRC
#'
#' @param ddrc a DDRC.df or DDRC.g matrix belonging to a cnr object
#'
#' @param base.ploidy expected cell ploidy, e.g. 2N = 2, 4N = 4.
#'
#' @return
#' 
#' returns a binary/incidence matrix for a DDRC object.  A value of 1 is
#'  returned for all values not equal to the cell ploidy.  Currently being
#' used to create an infScite table using clones. 
#'
#' @examples
#' 
#' data(cnr)
#' 
#' noisy.cells <- cnr$qc$cellID[cnr$qc$qc.status == "FAIL"]
#'
#' ## reduced pipeline to genrate DDRC clone profiles
#' cnr <- excludeCells(cnr, excl = noisy.cells)
#' cnr <- phylo_cnr(cnr, root.cell = "cell0")
#' cnr <- setBrayClusters(cnr)
#' cnr <- run_consensus_clustering(cnr, iters = 20, maxK = 40)
#' cnr <- doKSpectral(cnr)
#' cnr <- setKcc(cnr)
#' cnr <- cluster_heterogeneity(cnr, by = "category1",
#'           cluster_column = "ConsensusC")
#' cnr <- get_cluster_profiles(cnr)
#' 
#' binary.ddrc <- binaryDDRC(cnr$DDRC.df)
#' head(binary.ddrc)
#' 
#' @export
binaryDDRC <- function(ddrc, base.ploidy = 2) {
    z = matrix(0, nrow = nrow(ddrc), ncol = ncol(ddrc),
               dimnames = list(rownames(ddrc), colnames(ddrc)))
    z[ddrc != base.ploidy] <- 1
    z <- as.data.frame(z)
    z
} ## binaryDDRC