#' calculate.hclust
#'
#' Calculate hierarchical clustering for standard selections in
#' profiling script
#'
#'
#' @param dat data matrix (use log10 with pearson!)
#' @param method hierarchical clustering method (see ?hclust)
#' @param metric clustering metrics (spearman / pearson / euclidean)
#' @return hclust object for log10 and for absolute scale data
#'
#' @export
#' @examples
#' \dontrun{
#' data(peerj32)
#' dat <- peerj32$microbes
#' hc <- calculate.hclust(dat, 'complete', 'pearson')
#' }
#' @references See citation('microbiome')
#' @author Contact: Leo Lahti \email{microbiome-admin@@googlegroups.com}
#' @keywords utilities
calculate.hclust <- function(dat, method = "complete", metric = "pearson") {
if (metric == "euclidean") {
hc <- hclust(dist(t(dat)), method = method)
} else if (metric %in% c("spearman", "pearson")) {
hc <- hclust(as.dist(1 - cor(dat, use = "complete.obs",
method = metric)),
method = method)
} else {
stop("Provide proper metric for calculate.hclust!")
}
hc
}
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