Count barcodes directly from source FASTQ files

Usage

count_fastq(
  fq,
  samples,
  all_constructs,
  valid_barcodes,
  read_structure,
  verbose = TRUE
)

Arguments

fq: Path to one FASTQ file
samples: A sample sheet as data.frame in tsv format. Requires the columns 'sample_id', 'minigenes', 'rep', 'origin', 'barcode' `minigenes` lists construct libraries separated by `+`.
all_constructs: A named list of all construct libraries
valid_barcodes: A character vector of all possible construct barcodes
read_structure: A character string describing the FASTQ read structure. If missing, this will be inferred from the first reads in `fq`.
verbose: Whether to print progress messages (default: TRUE)

Value

A SummarizedExperiment object with counts and metadata `rowData` includes `unassigned_reads`, the number of reads with a matching construct barcode but no matching sample barcode. `metadata(dset)$unmapped_reads` records reads matching neither sample nor construct barcode, excluding reads too short to extract both barcodes.

Examples

samples = data.frame(sample_id="sample1", minigenes="pat1", rep="1",
    origin="library", barcode="GGG")
constructs = list(pat1=data.frame(gene_name="GENE1", mut_id="GENE1_A1V",
    pep_id="GENE1_A1V", pep_type="alt", tiled="ATGGCCGCC", barcode_1="AAAA"))
fq = tempfile(fileext=".fq")
writeLines(c("@r1", "GGGAAAA", "+", "IIIIIII", "@r2", "GGGAAAA", "+", "IIIIIII"), fq)
count_fastq(fq, samples, constructs, read_structure="3B4M", verbose=FALSE)
#> class: SummarizedExperiment 
#> dim: 1 1 
#> metadata(1): unmapped_reads
#> assays(1): counts
#> rownames(1): AAAA
#> rowData names(8): barcode unassigned_reads ... pep_type tiled
#> colnames(1): sample1
#> colData names(7): sample_id minigenes ... total_reads mapped_reads