Bioconductor Shortread

ShortRead

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

• Version: 1.70.0 · Bioconductor: 3.23 · R: ≥ 4.6
• Depends: BiocGenerics, BiocParallel, Biostrings, Rsamtools, GenomicAlignments
• Imports: Biobase, S4Vectors, IRanges, Seqinfo, GenomicRanges, pwalign, hwriter, lattice, latticeExtra
• Install: BiocManager::install("ShortRead")

When to Use

• Iterative FASTQ Processing: Processing massive FASTQ files in memory-efficient chunks using FastqStreamer() and yield().
• Random Subsampling: Drawing a random sample of reads from a FASTQ file using FastqSampler() for quick inspection.
• Quality Assessment: Generating HTML quality assessment reports across multiple FASTQ files using qa() and report().
• Filtering and Trimming: Removing low-quality reads or trimming tails using nFilter() and trimTailw() before writing back to disk with writeFastq().

When NOT to Use

• For whole-genome alignments or flexible pairwise alignment, use Biostrings or pwalign instead because ShortRead is designed for basic input, QA, and filtering rather than complex alignments.

Data Requirements

• Input: FASTQ files (e.g., .fastq, .fastq.gz) or legacy Solexa export files (s_N_export.txt).
• Output: Filtered FASTQ files, ShortReadQ objects, or HTML QA reports.
• Data Structures: Reads are represented as DNAStringSet objects and quality scores as FastqQuality or BStringSet objects.

Key Parameters

• fl: The file path to the FASTQ file being read or streamed.
• destination: The output file path used in writeFastq().
• type: The format type specified in qa() (e.g., type="fastq").
• dirPath: The directory path used in readXStringColumns() to locate files.
• pattern: The regular expression pattern used to match files in readXStringColumns().
• colClasses: A list specifying the class of each column to be read in readXStringColumns().

Best Practices

• Use FastqStreamer() in a repeat loop to process large FASTQ files in chunks, preventing memory exhaustion.
• Use FastqSampler() to draw a representative subset (e.g., 1M reads) for rapid quality assessment.
• Generate a QA report using qa() and view it in a browser using browseURL(report()) before starting downstream analysis.
• Check the quality score encoding of your FASTQ files using encoding(quality()) to ensure accurate quality filtering.

Common Pitfalls

• Out of Memory Errors: Attempting to load an entire massive FASTQ file into memory with readFastq(). Fix: Use FastqStreamer() to iterate through the file in manageable chunks.
• Incorrect Quality Trimming: Applying the wrong Phred score threshold because of unknown encoding. Fix: Verify the encoding using encoding(quality(fq)) before using trimTailw().
• Slow Text Parsing: Using base R functions to read specific columns of sequence text files. Fix: Use readXStringColumns() to quickly parse columns directly into DNAStringSet and BStringSet objects.

Alternatives

• Biostrings: For general sequence manipulation, pattern matching (matchPDict), and whole-genome alignments.
• pwalign: For flexible pairwise sequence alignment.

Citations

• Morgan M, et al. (2009) "ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data." Bioinformatics.

References

• Homepage: https://bioconductor.org/packages/ShortRead
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/ShortRead/inst/doc/Overview.pdf

Run this on BioMate

This skill is the knowledge layer — when, why, and how to use shortread. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open shortread on BioMate →