DADA2-SA.R

# This script largely modeled on examples from the DADA2 web site:
# https://benjjneb.github.io/dada2

library(dada2)

args <- commandArgs(trailingOnly = TRUE)
path <- args[1]
if (is.na(path)) {
    message("Input directory command line argument required.")
    quit()
}

filtpath <- file.path(path, "filtered")

d <- data.frame(
  # MLST loci parameters for Staphylococcus aureus
  genes <- c("arcC", "aroE", "glpF", "gmk", "pta", "tpi", "yqi"),
  mins <- c(435, 453, 450, 417, 468, 402, 507),
  maxs <- c(522, 456, 478, 420, 474, 402, 516))

for(i in seq_len(nrow(d))) {
    message(paste("====", d[i,1], "===="))
    output <- paste0("DADA2-SA-", d[i,1], "-out.tab")
    ddspath <- paste0(d[i,1], "-dds.rds")
    rdspath <- paste0(d[i,1], "-seqtab.rds")
    fns <- list.files(path, pattern=paste0("_", d[i,1], ".merged.fastq.gz"))
    numsamps = length(fns)
    message(paste("number of samples:", numsamps))
    head(fns)

    # filter and trim
    # for amplicon sequencing, leave out truncLen
    message("Filtering and trimming...")
    out <- filterAndTrim(file.path(path, fns), file.path(filtpath, fns),
        maxN=0, minLen=d[i,2], rm.phix=TRUE, maxEE=20.0,
        compress=TRUE, multithread=TRUE, verbose=TRUE)
    head(out)

    # learn error rates
    message("Learning error rates...")
    filts <- list.files(filtpath, pattern=paste0("_", d[i,1],
        ".merged.fastq.gz"), full.names=TRUE)
    sample.names <- sapply(strsplit(basename(filts), "[.]"), `[`, 1)
    names(filts) <- sample.names
    set.seed(100)
    err <- learnErrors(filts, nbases=1e8, multithread=TRUE,
        randomize=TRUE, verbose=TRUE)
    ##print(err)
    ##plotErrors(err, nominalQ=TRUE)

    # dereplication
    message("Dereplicating and inferring sequence variants...")
    derep <- derepFastq(filts, verbose=TRUE)

    # inference
    dds <- dada(derep, err=err, multithread=TRUE,
        selfConsist=TRUE, verbose=TRUE, pool=FALSE)
    saveRDS(dds, ddspath)
    dds[[1]]

    # construct an amplicon sequence variant table (ASV) table
    message("Making sequence table...")
    #seqtab <- readRDS(rdspath)
    seqtab <- makeSequenceTable(dds)
    saveRDS(seqtab, rdspath)
    # Inspect distribution of sequence lengths
    table(nchar(getSequences(seqtab)))

    # remove chimeras
    message("Removing chimeras...")
    seqtab.nochim <- removeBimeraDenovo(seqtab, method="per-sample",
        minFoldParentOverAbundance=1.0, minParentAbundance=8,
        allowOneOff=TRUE, minOneOffParentDistance=1, maxShift=16,
        multithread=TRUE, verbose=TRUE)
    dim(seqtab.nochim)
    message("Fraction kept:")
    sum(seqtab.nochim)/sum(seqtab)

    message("Writing output...")
    message(output)
    write.table(seqtab.nochim, file=output, col.names=NA, quote=FALSE, sep='\t')
}