--- a/phyloseq_from_dada2.R	Thu Mar 03 13:28:04 2022 +0000
+++ b/phyloseq_from_dada2.R	Fri Feb 09 21:42:24 2024 +0000
@@ -10,30 +10,25 @@
     make_option(c("--output"), action = "store", dest = "output", help = "RDS output")
 )
 
-parser <- OptionParser(usage = "%prog [options] file", option_list = option_list);
-args <- parse_args(parser, positional_arguments = TRUE);
-opt <- args$options;
-
+parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
+args <- parse_args(parser, positional_arguments = TRUE)
+opt <- args$options
 # The input sequence_table is an integer matrix
 # stored as tabular (rows = samples, columns = ASVs).
-seq_table_numeric_matrix <- data.matrix(read.table(opt$sequence_table, sep = "\t"));
-
+seq_table_numeric_matrix <- data.matrix(read.table(opt$sequence_table, sep = "\t"))
 # The input taxonomy_table is a table containing
 # the assigned taxonomies exceeding the minBoot
 # level of bootstrapping confidence. Rows correspond
 # to sequences, columns to taxonomic levels. NA
 # indicates that the sequence was not consistently
 # classified at that level at the minBoot threshold.
-tax_table_matrix <- as.matrix(read.table(opt$taxonomy_table, header = FALSE, sep = "\t"));
-
+tax_table_matrix <- as.matrix(read.table(opt$taxonomy_table, header = FALSE, sep = "\t"))
 # Construct a tax_table object.  The rownames of
 # tax_tab must match the OTU names (taxa_names)
 # of the otu_table defined below.
-tax_tab <- tax_table(tax_table_matrix);
-
+tax_tab <- tax_table(tax_table_matrix)
 # Construct an otu_table object.
-otu_tab <- otu_table(seq_table_numeric_matrix, taxa_are_rows = TRUE);
-
+otu_tab <- otu_table(seq_table_numeric_matrix, taxa_are_rows = TRUE)
 # Construct a phyloseq object.
-phyloseq_obj <- phyloseq(otu_tab, tax_tab);
-saveRDS(phyloseq_obj, file = opt$output, compress = TRUE);
+phyloseq_obj <- phyloseq(otu_tab, tax_tab)
+saveRDS(phyloseq_obj, file = opt$output, compress = TRUE)