R/long_distance.R

In bulksoil/tidyMB: A Set of Tools for Tidy Microbiome Analysis

#' Convert long data to a long dataframe of pairwise distances
#'
#' This function is a wrapper around Vegan's adonis function for performing PERMANOVA on tidy (long) data.
#' @param samples The column header for your sample identifiers. Defaults to SampleID
#' @param otus The column header for your OTU identifiers. Defaults to variable
#' @param value The column header for the OTU abundances. Defaults to RA
#' @param dist The distance metric options from vegan's vegdist(). Defaults to bray
#' @param keep_metadata Option to attach metadata onto the long distance object. Defaults to TRUE
#' @return S3 adonis object
#' @keywords adonis
#' @export
#' @examples
#' long_distance()

long_distance <- function(x, samples = "SampleID", otus = "variable", value = "RA", dist = "bray", keep_metadata = T) {
	
	metadata <- tidyMB::grab_metadata(x, samples = samples, otus = otus, value = value)
	wide_table <- tidyMB::widen(x, samples = samples, otus = otus, value = value, return_df = TRUE)

	dist_ <- as.matrix(vegan::vegdist(wide_table, dist = dist))

	row.names(dist_) <- metadata %>% dplyr::pull(`samples`)
	colnames(dist_) <- metadata %>% dplyr::pull(`samples`)

	dist_[upper.tri(dist_, diag = T)] <- NA

	Var1 <- "Var1"
	Var2 <- "Var2"

	dist_long <- reshape2::melt(dist_) %>% na.omit()
	if(keep_metadata) {
		return(dist_long %>% 
					dplyr::inner_join(metadata, by = setNames(samples, Var1)) %>%
					dplyr::inner_join(metadata, by = setNames(samples, Var2)))
		} else {
			return(dist_long)
		}

	
}