R/symmetricize.R

In MalathiSIDona/pathDESeq: Pathway-Based Differential Expression Analysis for RNA-Seq Data

#' Make a matrix symmetric
#'
 
#' Make the matrix symmetric by making all "mirrored" positions consistent. A variety of methods are provided to make the matrix symmetrical.

#' @param matrix The matrix to make symmatric

#' @param method The method to use to make the matrix symmetric. Default is to take the maximum. 

#' \itemize{
#' 	\item{"max"} {For each position, \eqn{m_{i,j}}, use the maxiumum of \eqn{(m_{i,j}, m_{j,i})}}

#' 	\item{"min"} {For each position, \eqn{m_{i,j}}, use the minimum of \eqn{(m_{i,j}, m_{j,i})}}

#' 	\item{"avg"} {For each position, \eqn{m_{i,j}}, use the mean: \eqn{(m_{i,j} + m_{j,i})/2}}

#' 	\item{"ld"} {Copy the lower triangular portion of the matrix to the upper triangular portion.}

#' 	\item{"ud"} {Copy the upper triangular portion of the matrix to the lower triangular portion.}

#' }

#' @param adjacencyList Logical. If false, returns the symmetric matrix (the same format as the input). 
#If true, returns an adjacency list representing the upper triangular portion of the adjacency matrix with
# addressing based on the row.names of the matrix provided.

#' @return The symmetric matrix

#' @export

#' @author Jeffrey D. Allen \email{Jeffrey.Allen@@UTSouthwestern.edu}

#' @examples
#' 
#Create a sample 3x3 matrix

#' mat <- matrix(1:9, ncol=3)
#'
 
#' 
#Copy the upper diagonal portion to the lower

#' symmetricize(mat, "ud")
#' 

#' #Take the average of each symmetric location

#' symmetricize(mat, "avg")

#' 

symmetricize <-
function (matrix, method = c("max", "min", "avg", "ld", "ud"), adjacencyList = FALSE) {
    method <- match.arg(method)
    if (missing(matrix)) {
        stop("You must provide a matrix to symmetricize.")
    }
    x <- matrix
    if (method == "ld") {
        x[matrix(c(col(x)[lower.tri(x)], row(x)[lower.tri(x)]), 
            ncol = 2)] <- x[matrix(c(row(x)[lower.tri(x)], col(x)[lower.tri(x)]), 
            ncol = 2)]
    }
    if (method == "ud") {
        x[matrix(c(col(x)[upper.tri(x)], row(x)[upper.tri(x)]), 
            ncol = 2)] <- x[matrix(c(row(x)[upper.tri(x)], col(x)[upper.tri(x)]), 
            ncol = 2)]
    }
    if (method == "max" || method == "min" || method == "avg") {
        ldi <- matrix(c(row(x)[lower.tri(x)], col(x)[lower.tri(x)]), 
            ncol = 2)
        udi <- matrix(c(row(x)[upper.tri(x)], col(x)[upper.tri(x)]), 
            ncol = 2)
        udi <- udi[order(udi[, 1], udi[, 2]), ]
        ud <- x[udi]
        ld <- x[ldi]
        if (method == "max") {
            x[ldi] <- apply(rbind(ld, ud), 2, max)
            x[udi] <- apply(rbind(ld, ud), 2, max)
        }
        if (method == "min") {
            x[ldi] <- apply(rbind(ld, ud), 2, min)
            x[udi] <- apply(rbind(ld, ud), 2, min)
        }
        if (method == "avg") {
            x[ldi] <- apply(rbind(ld, ud), 2, mean)
            x[udi] <- apply(rbind(ld, ud), 2, mean)
        }
    }
    if (!adjacencyList) {
        return(x)
    }
    else {
        if (is.null(rownames(matrix))) {
            stop("You requested adjacency list format, but the matrix provided has no (row) names.")
        }
        names <- rownames(matrix)
        add <- getTableAddressing(names)
        toReturn <- (cbind(add, x[upper.tri(x)]))
        colnames(toReturn) <- c("Source", "Dest", "Symmetric")
        return(toReturn)
    }
}