ncyc2meco {file2meco}

Transform 'NCycDB' or 'PCycDB' metagenomic abundance to 'microtable' object.

Description

Transform 'NCycDB' or 'PCycDB' metagenomic abundance to microtable object. The function can identify the mapping database according to the gene names of input feature abundance table. Reference: Qichao et al. (2019) <doi: 10.1093/bioinformatics/bty741> and Zeng et al. (2022) <doi: 10.1186/s40168-022-01292-1>.

Usage

ncyc2meco(feature_table, sample_table = NULL, match_table = NULL, ...)

Arguments

feature_table

'NCycDB' or 'PCycDB' output abundance table, see the example file.

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 readxl package to be installed; 3) data.frame object from R. A file path must be tab or comma seperated file, generally, a file with suffix "tsv" or "csv".

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. A file path must be tab or comma seperated file, e.g. a file with suffix "tsv" or "csv".

...

parameter passed to microtable$new function of microeco package, such as auto_tidy parameter.

Value

microtable object.

Examples

# NCycDB
abund_file_path <- system.file("extdata", "example_Ncyc_table.tsv", package="file2meco")
sample_file_path <- system.file("extdata", "example_metagenome_sample_info.tsv", 
  package="file2meco")
match_file_path <- system.file("extdata", "example_metagenome_match_table.tsv", package="file2meco")
library(microeco)
library(file2meco)
library(magrittr)
ncyc2meco(abund_file_path)
test <- ncyc2meco(abund_file_path, sample_table = sample_file_path, 
  match_table = match_file_path)
test$tidy_dataset()
# use split_group = TRUE to calculate the pathway abundance with multipe map correspondance
test$cal_abund(select_cols = 1, rel = TRUE, split_group = TRUE, split_column = "Pathway")
test$taxa_abund$Pathway %<>% .[!grepl("unclass", rownames(.)), ]
test1 <- trans_abund$new(test, taxrank = "Pathway")
test1$plot_bar(bar_type = "notfull")
# for gene abundance, no splitting on the Pathway
test$cal_abund(select_cols = 1:2, rel = TRUE, split_group = FALSE)
test$taxa_abund$Gene %<>% .[!grepl("unclass", rownames(.)), ]
test1 <- trans_abund$new(test, taxrank = "Gene")
test1$plot_bar(bar_type = "notfull")

# PCycDB
abund_file_path <- system.file("extdata", "example_Pcyc_table.tsv", package="file2meco")
test <- ncyc2meco(abund_file_path)
test$tidy_dataset()
# show pathway abundance
test$cal_abund(select_cols = 1, rel = TRUE, split_group = TRUE, split_by = "&&", 
    split_column = "Pathway")
test$taxa_abund$Pathway %<>% .[!grepl("unclass|Others", rownames(.)), ]
test1 <- trans_abund$new(test, taxrank = "Pathway")
test1$plot_bar(bar_type = "notfull")
# show gene abundance
test$cal_abund(select_cols = 2, rel = TRUE, split_group = FALSE)
test$taxa_abund$Gene %<>% .[!grepl("unclass", rownames(.)), ]
test1 <- trans_abund$new(test, taxrank = "Gene")
test1$plot_bar(bar_type = "notfull")