#'Data normalisation
#'
#'This function normalises taxa abundance
#'
#' @param physeq (Required). A \code{phyloseq} object containing merged information of abundance,
#' taxonomic assignment, sample data including the measured variables and categorical information
#' of the samples, and / or phylogenetic tree if available.
#' @param method (Required). A \code{method} to used to normalise the data. Available methods include:
#' "edgeRnorm", "varstab", "randomsubsample", "proportion" .
#' @return Returns a phyloseq object whose abundance data is normalised.
#' @examples
#' data(pitlatrine)
#' physeq<-data(pitlatrine)
#' physeq <- normalise_data(physeq,method = "randomsubsample")
#' physeq <- normalise_data(physeq,method = "edgeRnorm")
#' physeq <- normalise_data(physeq,method = "proportion")
#'
#' @references \url{http://userweb.eng.gla.ac.uk/umer.ijaz/}, Umer Ijaz, 2015
#'
#' @author Alfred Ssekagiri \email{assekagiri@gmail.com}, Umer Zeeshan Ijaz \email{Umer.Ijaz@glasgow.ac.uk}
#'
#' @export normalise_data
#'
normalise_data <- function(physeq, norm.method, ...){
norm.method = match.arg(norm.method,c("edgernorm","varstab","randomsubsample",
"proportion","relative","log-relative","scale"))
switch(norm.method,
"randomsubsample"=randomsubsample(physeq),
"proportion"=proportion(physeq),
"varstab"=deseq_varstab(physeq, ...),
"edgernorm"=edgeRnorm(physeq, ...),
"log-relative"=log_relative(physeq, ...),
"relative"=relative(physeq, ...),
"scale"=scale.meta(physeq, ...)
)
}
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