R/mpa2meco.R

In file2meco: Transform Files to 'microtable' Object with 'microeco' Package

#' Transform metagenomic classification results of 'mpa' format to 'microtable' object.
#'
#' @description
#' Transform the classification results of mpa (MetaPhlAn) format to microtable object,
#' such as MetaPhlAn and Kraken2 results. Kraken2 results can be obtained by merge_metaphlan_tables.py from MetaPhlAn or 
#' combine_mpa.py from KrakenTools (https://ccb.jhu.edu/software/krakentools/).
#' The algorithm of Kraken2 determines that the abundance of a taxon is not equal to the sum of abundances of taxa in its subordinate lineage.
#' So the default tables in taxa_abund of return microtable object are extracted from the abundances of raw file. 
#' It is totally different with the return taxa_abund of cal_abund function, 
#' which sums the abundances of taxa at different taxonomic levels based on the taxonomic table and the otu_table 
#' (i.e., taxa abundance table at a specified level, e.g., 's__').
#' 
#' @param feature_table 'mpa' format abundance table, see the example.
#' @param sample_table default NULL; sample metadata table; If provided, must be one of the several types of formats: 
#'   1) comma seperated file with the suffix csv or tab seperated file with suffix tsv/txt; 
#'   2) Excel type file with the suffix xlsx or xls; require \code{readxl} package to be installed; 
#'   3) \code{data.frame} object from R.
#' @param match_table default NULL; a two column table used to replace the sample names in abundance table; Must be two columns without column names;
#'    The first column must be raw sample names same with those in feature table, 
#'    the second column must be new sample names same with the rownames in sample_table; Please also see the example files.
#' @param use_level default "s__"; the prefix parsed for the otu_table and tax_table; must be one of 'd__', 'k__', 'p__', 'c__', 'o__', 'f__', 'g__' and 's__'.
#' @param ... parameter passed to microtable$new function of microeco package, such as auto_tidy parameter.
#' @return microtable object.
#' @examples
#' \donttest{
#' library(microeco)
#' library(file2meco)
#' library(magrittr)
#' # use Kraken2 file stored inside the package
#' abund_file_path <- system.file("extdata", "example_kraken2_merge.txt", package="file2meco")
#' mpa2meco(abund_file_path)
#' # add sample information table
#' sample_file_path <- system.file("extdata", "example_metagenome_sample_info.tsv", 
#'   package="file2meco")
#' # sample names are different between abund_file_path and sample_file_path; 
#' # use a matching table to adjust them
#' match_file_path <- system.file("extdata", "example_metagenome_match_table.tsv", package="file2meco")
#' test <- mpa2meco(abund_file_path, sample_table = sample_file_path, 
#'   match_table = match_file_path, use_level = "s__")
#' # make the taxonomy standard for the following analysis
#' test$tax_table %<>% tidy_taxonomy
#' test$tidy_dataset()
#' # convert the data of default taxa_abund to relative abundance
#' test$taxa_abund %<>% lapply(function(x){apply(x, 2, function(y){y/sum(y)})})
#' # calculate taxa_abund with specified level instead of raw kraken results
#' test1 <- clone(test)
#' test1$cal_abund()
#' identical(test$taxa_abund$Kingdom, test1$taxa_abund$Kingdom)
#' }
#' @export
mpa2meco <- function(feature_table, sample_table = NULL, match_table = NULL, use_level = "s__", ...){
	abund_raw <- readLines(feature_table)
	header_line <- unlist(strsplit(abund_raw[1], "\t"))
	total_abund <- sapply(abund_raw[-1], function(x){unlist(strsplit(x, "\t"))}) %>% 
		t %>% 
		as.data.frame %>%
		`colnames<-`(header_line) %>%
		`row.names<-`(.[, 1]) %>%
		.[, -1, drop = FALSE] %>%
		microeco::dropallfactors(unfac2num = TRUE)

	if(! use_level %in% c('d__', 'k__', 'p__', 'c__', 'o__', 'f__', 'g__', 's__')){
		stop("use_level must be one of 'd__', 'k__', 'p__', 'c__', 'o__', 'f__', 'g__' and 's__'!")
	}
	# Because parts of taxonomy are missing, we extract for each taxonomy
	# determine the prefix of Bacteria, Archaea or Fungi
	if(any(grepl("d__Bacteria|d__Archaea|d__Fungi", rownames(total_abund)))){
		replace_level <- c('d__', 'p__', 'c__', 'o__', 'f__', 'g__', 's__')
		if(use_level == "k__"){
			use_level = "d__"
		}
	}else{
		replace_level <- c('k__', 'p__', 'c__', 'o__', 'f__', 'g__', 's__')
		if(use_level == "d__"){
			use_level = "k__"
		}
	}
	all_taxonomic_levels <- c("Kingdom","Phylum","Class","Order","Family","Genus","Species")
	# extract species data to create microtable object
	abund_table_taxa <- total_abund[grepl(paste0(use_level, "(?!.*\\|).*"), rownames(total_abund), perl = TRUE), , drop = FALSE]
	# generate taxonomic table
	raw_taxonomy <- rownames(abund_table_taxa)

	col_number <- which(replace_level %in% use_level)
	message("Generate otu_table at ", all_taxonomic_levels[col_number], " level ...")

	taxonomy <- matrix(nrow = nrow(abund_table_taxa), ncol = col_number)
	colnames(taxonomy) <- all_taxonomic_levels[1:col_number]
	rownames(taxonomy) <- raw_taxonomy
	for(i in 1:col_number){
		tmp <- replace_level[i]
		taxonomy[, i] <- gsub(paste0(".*(", tmp, ".*?)(\\|.*|$)"), "\\1", raw_taxonomy, ignore.case = TRUE)
		taxonomy[, i][!grepl(tmp, taxonomy[, i])] <- ""
	}
	taxonomy %<>% as.data.frame(stringsAsFactors = FALSE) %>% microeco::tidy_taxonomy()
	tax_table <- taxonomy
	message("Generate tax_table ...")
	# generate taxa_abund from raw data
	taxa_abund <- list()
	for(i in 1:col_number){
		tmp <- replace_level[i]
		taxa_abund[[all_taxonomic_levels[i]]] <- total_abund[grepl(paste0(tmp, "(?!.*\\|).*"), rownames(total_abund), perl = TRUE), , drop = FALSE]
	}
	
	# first check the match_table
	if(!is.null(match_table)){
		abund_table_taxa <- check_match_table(match_table = match_table, abund_new = abund_table_taxa)
		for(i in names(taxa_abund)){
			taxa_abund[[i]] <- check_match_table(match_table = match_table, abund_new = taxa_abund[[i]])
		}
	}
	# read sample metadata table
	if(!is.null(sample_table)){
		sample_table <- check_sample_table(sample_table = sample_table)
	}
	# create microtable object
	dataset <- microtable$new(otu_table = abund_table_taxa, sample_table = sample_table, tax_table = tax_table, ...)
	message("Create the microtable object ...")

	dataset$taxa_abund <- taxa_abund
	message("Generate taxa_abund list using raw taxonomic abundance of the input file ...")
	
	dataset
}