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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/phyloseq commit 5ec9f9e81bb9a42dec5c331dd23215ca0b027b2b
author iuc
date Sat, 16 Mar 2024 07:56:05 +0000
parents 92e77800ef2c
children
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11d43fa12aab "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/phyloseq commit d1004c06207be773c278e12745aada276b63172e"
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1 #!/usr/bin/env Rscript
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3 suppressPackageStartupMessages(library("optparse"))
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4 suppressPackageStartupMessages(library("phyloseq"))
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5 suppressPackageStartupMessages(library("tidyverse"))
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7 option_list <- list(
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8 make_option(c("--sequence_table"), action = "store", dest = "sequence_table", help = "Input sequence table"),
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9 make_option(c("--taxonomy_table"), action = "store", dest = "taxonomy_table", help = "Input taxonomy table"),
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10 make_option(c("--sample_table"), action = "store", default = NULL, dest = "sample_table", help = "Input sample table"),
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11 make_option(c("--output"), action = "store", dest = "output", help = "RDS output")
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12 )
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14 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
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15 args <- parse_args(parser, positional_arguments = TRUE)
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16 opt <- args$options
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17 # The input sequence_table is an integer matrix
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18 # stored as tabular (rows = samples, columns = ASVs).
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19 seq_table_numeric_matrix <- data.matrix(read.table(opt$sequence_table, header = T, sep = "\t", row.names = 1, check.names = FALSE))
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20 # The input taxonomy_table is a table containing
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21 # the assigned taxonomies exceeding the minBoot
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22 # level of bootstrapping confidence. Rows correspond
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23 # to sequences, columns to taxonomic levels. NA
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24 # indicates that the sequence was not consistently
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25 # classified at that level at the minBoot threshold.
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26 tax_table_matrix <- as.matrix(read.table(opt$taxonomy_table, header = T, sep = "\t", row.names = 1, check.names = FALSE))
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27 # Construct a tax_table object. The rownames of
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28 # tax_tab must match the OTU names (taxa_names)
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29 # of the otu_table defined below.
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30 tax_tab <- tax_table(tax_table_matrix)
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32 # Construct an otu_table object.
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33 otu_tab <- otu_table(seq_table_numeric_matrix, taxa_are_rows = TRUE)
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35 # Construct a phyloseq object.
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36 phyloseq_obj <- phyloseq(otu_tab, tax_tab)
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37 if (!is.null(opt$sample_table)) {
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38 sample_tab <- sample_data(
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39 read.table(opt$sample_table, header = T, sep = "\t", row.names = 1, check.names = FALSE)
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40 )
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41 phyloseq_obj <- merge_phyloseq(phyloseq_obj, sample_tab)
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42 }
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44 # use short names for our ASVs and save the ASV sequences
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45 # refseq slot of the phyloseq object as described in
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46 # https://benjjneb.github.io/dada2/tutorial.html
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47 dna <- Biostrings::DNAStringSet(taxa_names(phyloseq_obj))
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48 names(dna) <- taxa_names(phyloseq_obj)
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49 phyloseq_obj <- merge_phyloseq(phyloseq_obj, dna)
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50 taxa_names(phyloseq_obj) <- paste0("ASV", seq(ntaxa(phyloseq_obj)))
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52 print(phyloseq_obj)
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54 # save R object to file
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55 saveRDS(phyloseq_obj, file = opt$output, compress = TRUE)