R/abundance_core.R

In MayaGans/CoreMicro: Testing Widely Used Core Microbiome Assignment Methods

#' Summation of Reads:
#'
#' @description This method assigns taxa to the core if they are in the top X% of reads.
#' Taxa are ranked in abundance and the cumulative sum is recorded.
#' Any taxa which appears before some cutoff percentage is included in the core.
#' In this example, a taxa will be assigned to the core if they account for the first 75% of the reads
#'
#' @param otu_table a dataframe of OTUs where the first row is the OTU ID and column names refer to sites
#' @param readn count of reads needed
#'
#' @param taxa_as_rows \code{logical} data must be in a format where the taxa are rows
#' and the sites are columns. The default value is \code{TRUE},
#' if \code{FALSE} data will be transposed for downstream analysis.
#'
#' @return the names of OTUs which meet the proportion of reads criteria
#'
#' @examples
#' abundance_core(arabidopsis)
#'
#' @export

abundance_core <- function(otu_table, readn = 0.75, taxa_as_rows =TRUE) {

  # transpose data if rows are not taxa
  if (!taxa_as_rows) otu_table <- transpose_taxa(otu_table)

  # rename first column `X`
  names(otu_table)[1] <- "X"

  otu_table %>%
    tidyr::pivot_longer(-.data$X) %>%
    dplyr::group_by(.data$X) %>%
    dplyr::summarise(otuappearance = sum(.data$value)) %>%
    dplyr::arrange(-.data$otuappearance) %>%
    dplyr::mutate(s = sum(.data$otuappearance),
           prop = .data$otuappearance/.data$s,
           cumsum = cumsum(.data$prop)) %>%
    dplyr::filter(cumsum <= readn) %>%
    dplyr::pull(.data$X)
}