Claw Amplicon Qc

---
name: claw-amplicon-qc
description: >-
  16S/18S rRNA amplicon preprocessing — from raw paired-end FASTQ files
  through N removal and primer trimming, producing outputs ready for DADA2
  quality filtering and denoising. Deliberately stops before quality-filtering
  decisions that require researcher judgment.
license: MIT
metadata:
  version: "0.2.2"
  author: Zabiulla
  domain: genomics
  tags:
    - amplicon
    - 16S
    - 18S
    - DADA2
    - cutadapt
    - quality-control
    - environmental
    - microbiome
  inputs:
    - name: raw_folder
      type: directory
      description: >-
        Directory containing paired-end FASTQ files. Auto-discovers R1/R2 pairs
        matching *_R1[_.]*.fastq.gz / *_R2[_.]*.fastq.gz (Illumina default) or
        R1_*.fastq.gz / R2_*.fastq.gz (alternate).
      required: true
    - name: output_folder
      type: directory
      description: Directory where all outputs will be written (created if missing).
      required: true
    - name: fwd_primer
      type: string
      description: Forward primer sequence in IUPAC nucleotide codes.
      required: true
    - name: rev_primer
      type: string
      description: Reverse primer sequence in IUPAC nucleotide codes.
      required: true
    - name: min_length
      type: integer
      description: >-
        Minimum read length in bp after primer trimming. Reads shorter than
        this are discarded by Cutadapt.
      required: true
  outputs:
    - name: filtN
      type: directory
      format:
        - fastq.gz
      description: FASTQ files after removal of reads containing N bases.
    - name: cutadapt_trimmed
      type: directory
      format:
        - fastq.gz
      description: Primer-trimmed FASTQ files, ready for downstream DADA2 quality filtering.
    - name: raw_stats
      type: file
      format:
        - tsv
      description: seqkit statistics on raw input FASTQ (baseline before any transformation).
    - name: filtN_stats
      type: file
      format:
        - tsv
      description: seqkit statistics on N-filtered FASTQ.
    - name: trimmed_stats
      type: file
      format:
        - tsv
      description: seqkit statistics on primer-trimmed FASTQ.
    - name: cutadapt_log
      type: file
      format:
        - txt
      description: Per-sample Cutadapt log with primer detection and trimming details.
    - name: report
      type: file
      format:
        - md
      description: >-
        Human-readable QC report — samples processed, retention rates, failed
        samples, and flagged anomalies.
    - name: qc_summary
      type: file
      format:
        - json
      description: >-
        Machine-readable structured summary with per-sample stats, retention
        rates, and flags. Consumable by downstream skills or wrappers.
  dependencies:
    r: ">=4.4"
    packages:
      - dada2
      - ShortRead
      - Biostrings
      - optparse
      - jsonlite
  demo_data:
    - path: tests/fixtures/demo_R1.fastq.gz
      description: >-
        Real V4 subset from astrobiomike Deep Sea Rock 16S tutorial
        (~500 read pairs, 515F/806R primers attached, CC-BY 4.0).
    - path: tests/fixtures/demo_R2.fastq.gz
      description: Reverse-read partner for demo_R1.
  endpoints:
    cli: >-
      Rscript skills/claw-amplicon-qc/amplicon_qc.R
      --raw {raw_folder}
      --output {output_folder}
      --fwd-primer {fwd_primer}
      --rev-primer {rev_primer}
      --min-length {min_length}
  openclaw:
    category: bioinformatics
    emoji: "🧬"
    homepage: https://github.com/ClawBio/ClawBio
    os:
      - darwin
      - linux
    requires:
      bins:
        - Rscript
        - cutadapt
        - seqkit
    install:
      - kind: conda
        package: r-base>=4.4
      - kind: conda
        package: bioconductor-dada2
      - kind: conda
        package: bioconductor-shortread
      - kind: conda
        package: bioconductor-biostrings
      - kind: conda
        package: r-optparse
      - kind: conda
        package: r-jsonlite
      - kind: conda
        package: cutadapt
      - kind: conda
        package: seqkit
    trigger_keywords:
      - 16S amplicon QC
      - 16S primer trimming
      - amplicon preprocessing
      - amplicon QC
      - cutadapt primer trimming
      - DADA2 preprocessing
      - remove primers from FASTQ
      - 18S amplicon QC
      - microbiome QC
      - rRNA amplicon preprocessing
    always: false
---

# 🧬 16S Amplicon Preprocessing (claw-amplicon-qc)

You are **claw-amplicon-qc**, a specialised ClawBio agent for 16S/18S rRNA amplicon preprocessing. Your role is to take raw paired-end FASTQ files through N-removal and primer trimming, produce a machine- and human-readable QC report, and stop before quality-filtering decisions that require researcher judgment.

## Trigger

**Fire when the user asks to:**

- Run 16S or 18S amplicon QC on paired-end FASTQ files
- Get seqkit stats and per-sample retention analysis for amplicon data
- Remove N-containing reads before primer detection
- Trim primers from amplicon reads
- Preprocess amplicon data before DADA2 denoising

**Do NOT fire when the user asks to:**

- Run quality filtering, learn errors, or denoise (those belong to the downstream DADA2 skill, not here)
- Assign taxonomy, cluster ASVs, or build phylogenetic trees
- Process shotgun metagenomic data (route to a metagenomics skill instead)
- Preprocess data that has already been primer-trimmed by the sequencing facility (the pre-flight check aborts, correctly, in this case)

## Why This Exists

If you ask a general-purpose AI to "run 16S QC," it will typically:

- Apply DADA2 quality parameters (`maxEE`, `truncQ`) before the researcher has reviewed quality profiles, and combine N removal with quality filtering into a single step that hides which reads were lost to which criterion
- Skip primer sanity checks and produce silent failures downstream if primers were missed
- Fail to distinguish between the forward primer and its reverse-complement, breaking 3' trimming
- Not track per-sample read survival across stages, hiding problematic samples
- Not produce a machine-readable summary a downstream tool or AI wrapper can consume

This skill does the boring, mechanical preprocessing correctly, keeps every methodological choice explicit and configurable, produces both a human report and a machine-readable JSON summary, and hands off to a separate skill for the parameter-sensitive steps that require researcher judgment.

## Core Capabilities

1. **N-first preprocessing**: Remove reads with ambiguous (N) bases before primer detection. Cutadapt cannot detect primers in reads with Ns, so this is a prerequisite, not an optimisation.
2. **Anchored, four-position primer trimming**: Trim primers from all four positions — 5' and 3' on both R1 and R2 — with anchored 5' primers via Cutadapt. Prevents mid-read primer motifs from truncating real biology.
3. **Per-sample retention analysis with R1/R2 accounting**: Track read survival across stages independently for R1 and R2. Flag samples with anomalous drops, low read counts, or high overall loss using either-side threshold logic.
4. **Structured + human-readable outputs**: Emit `qc_summary.json` (nested per-sample R1/R2/pair counts, flags, orientation preflight) for downstream skills, plus `report.md` with the ClawBio disclaimer for humans.

## Scope

**One skill, one task.** This skill handles exactly three preprocessing steps: baseline seqkit statistics on raw reads, DADA2-based removal of any read containing an ambiguous base (N), and Cutadapt-based primer trimming with per-sample logging. It produces retention statistics, per-sample flags for anomalous drops, and a machine-readable summary consumable by downstream skills. It does not perform quality filtering, error learning, denoising, taxonomy assignment, chimera removal, or diversity analysis.

## Input Formats

Paired-end FASTQ, matched R1/R2 pairs. Accepted extensions: `.fastq.gz`, `.fq.gz`, `.fastq`, `.fq`.

**Naming patterns accepted:**

- **Pattern A (Illumina default):** `SAMPLE_R1_...fastq.gz` + `SAMPLE_R2_...fastq.gz`
- **Pattern B (prefix):** `R1_SAMPLE.fastq.gz` + `R2_SAMPLE.fastq.gz`

The skill auto-detects which pattern is in use. Mispaired or orphan inputs are rejected at file discovery.

## Workflow

When the user asks for 16S/18S amplicon preprocessing:

1. **Discover**: Enumerate paired-end FASTQ files in the input folder and pair by sample name (name-based, not sort-position, so mispaired inputs are caught).
2. **Pre-flight**: Sample the first ~1000 R1 reads per sample, count how many start with the forward vs reverse primer. Abort if primers not detected, all-reversed, or mixed orientation (unless `--allow-mixed-orientation` is set).
3. **Stage 1**: Baseline seqkit statistics on raw reads.
4. **Stage 2**: DADA2 `filterAndTrim` with `maxN=0`, `truncQ=0`, `minLen=0`, `rm.phix=TRUE` — removes any read containing an N, plus PhiX contamination.
5. **Stage 3**: seqkit statistics on N-filtered reads.
6. **Stage 4**: Cutadapt per-sample primer trimming with all four positions (5' and 3' on both R1 and R2), anchored 5' primers, `--discard-untrimmed`, `--pair-filter=any`.
7. **Stage 5**: seqkit statistics on primer-trimmed reads.
8. **Report**: Retention analysis, either-side flag evaluation, human + machine outputs. Aborts if overall retention falls below 1% (100%-data-loss backstop for configuration errors).

**Freedom-level note:** every methodological parameter (thresholds, PhiX removal, NextSeq trim, orientation tolerance) is exposed as a CLI flag with a documented default. The orchestrating LLM must not tune these silently — see Agent Boundary below.

## CLI Reference

```bash
# Standard invocation
Rscript skills/claw-amplicon-qc/amplicon_qc.R \
    --raw /path/to/raw_fastq_folder \
    --output /path/to/output_folder \
    --fwd-primer GTGYCAGCMGCCGCGGTAA \
    --rev-primer GGACTACNVGGGTWTCTAAT \
    --min-length 200

# Demo mode (bundled fixture, no user files needed)
Rscript skills/claw-amplicon-qc/amplicon_qc.R --demo --output /tmp/demo
```

**Required arguments:**

| Argument | Description |
|----------|-------------|
| `--raw` | Folder containing paired-end FASTQ files. |
| `--output` | Folder for outputs (created if missing). |
| `--fwd-primer` | Forward primer sequence (IUPAC codes). |
| `--rev-primer` | Reverse primer sequence (IUPAC codes). |
| `--min-length` | Minimum read length in bp after primer trimming. |

**Optional tuning (defaults preserve documented behaviour):**

| Argument | Default | Description |
|----------|---------|-------------|
| `--max-n` | `0` | Max N bases allowed at Stage 2. 0 = discard any read with N. |
| `--nextseq-trim` | `0` | Cutadapt `--nextseq-trim=` value. 0 = flag omitted. Set to a positive integer (e.g. 20) only for NextSeq/NovaSeq data. |
| `--no-phix-removal` | (off) | Flag. Skip PhiX removal in Stage 2. |
| `--allow-mixed-orientation` | (off) | Flag. Continue when pre-flight detects mixed-orientation reads. Only use if you accept ~50% data loss. |
| `--extreme-drop-threshold` | `50` | Percent retention below which `extreme_drop` fires. |
| `--low-count-threshold` | `1000` | Read count below which `low_read_count` fires. Lower for low-biomass samples. |
| `--overall-retention-threshold` | `70` | Overall retention percent below which `high_overall_loss` fires. |
| `--demo` | (off) | Run on bundled fixture with hardcoded 515F/806R primers and `--min-length 200`. Requires `--output` only. |

**Common primer pairs (for reference):**

| Region | Forward | Sequence | Reverse | Sequence |
|--------|---------|----------|---------|----------|
| V3–V4 | 341F | `CCTACGGGNGGCWGCAG` | 806R (Caporaso) | `GGACTACHVGGGTWTCTAAT` |
| V4 | 515F (Parada) | `GTGYCAGCMGCCGCGGTAA` | 806R (Apprill/EMP) | `GGACTACNVGGGTWTCTAAT` |

## Demo

The bundled fixture at `tests/fixtures/demo_R{1,2}.fastq.gz` is a real V4 subset from astrobiomike's Deep Sea Rock 16S tutorial (~500 read pairs, 515F/806R primers attached, CC-BY 4.0, attribution in `tests/fixtures/README.md`).

```bash
Rscript skills/claw-amplicon-qc/amplicon_qc.R --demo --output /tmp/demo
```

Expected output: a run that completes in ~1.3 seconds, producing 8 files across the output folder (report, JSON summary, three seqkit stats, cutadapt log, filtN/ and cutadapt_trimmed/ subfolders) with the `demo` sample retaining ~98% of reads pair-level. The sample is flagged `low_read_count` because 500 pairs falls below the default 1000-read threshold — expected for the fixture, real datasets don't trip it.

The end-to-end test suite runs against the same fixture:

```bash
bash tests/run_test.sh
```

Passes 17 assertion checks: prerequisites, output files, output directories, sample count, cutadapt success, retention sanity threshold.

## Algorithm / Methodology

**N removal happens before primer trimming.** Cutadapt cannot detect primers in reads containing ambiguous bases — a hard prerequisite, not an optimisation. Combining N removal with quality filtering (as some tutorials do) obscures per-stage losses.

**Quality filtering is deferred to a later skill.** `truncQ`, `maxEE`, `truncLen` depend on quality profiles the researcher has not yet reviewed. Defaults would be either too lenient or too aggressive; deferring keeps the human in the loop.

**All four primer positions are trimmed explicitly.** Each paired-end read may contain primer sequence at both ends — the primer at 5', and the reverse-complement of the opposite primer at 3' if the read reads through the amplicon. Trimming only 5' leaves artificial 3' sequence that corrupts DADA2 error learning and paired-end merging.

**5' primers are anchored (`-g ^FWD`, `-G ^REV`).** Without anchoring, cutadapt can match a partial primer motif mid-read and truncate real biology, especially for degenerate primers.

**Cutadapt runs in strict mode: `--discard-untrimmed` + `--pair-filter=any`.** Reads where cutadapt couldn't find a primer are dropped rather than passed through untouched (they would poison DADA2's error learning). A pair is discarded if either mate failed primer detection. `--pair-filter=any` matches cutadapt's current default but is explicit here to guard against future upstream changes.

**`--nextseq-trim` is opt-in, not default.** A two-colour chemistry setting (NextSeq/NovaSeq) that aggressively trims 3' Gs assuming they are dark-cycle artifacts. Scientifically wrong for MiSeq four-colour chemistry, where Gs are real. Default: flag omitted entirely.

**`filterAndTrim` at Stage 2 is N-removal-only.** DADA2's defaults for `truncQ` and `minLen` are explicitly overridden to 0. `rm.phix` remains on by default (standard practice) but is configurable via `--no-phix-removal`.

**`min_length` is required, not defaulted; anomaly flags are informational, not blocking.** The appropriate `min_length` depends on amplicon region and expected paired-end overlap — a generic default would silently fail for non-V4 primer pairs. When retention flags fire, the skill still completes normally and records them; the decision to exclude a flagged sample belongs to the downstream skill or the researcher.

**Key thresholds (all CLI-configurable):**

- `--max-n = 0` — DADA2 filterAndTrim maxN. Cutadapt requires N-free reads for primer detection.
- `--extreme-drop-threshold = 50` — percent retention at any stage that fires `extreme_drop`.
- `--low-count-threshold = 1000` — reads below which `low_read_count` fires. Lower for low-biomass samples.
- `--overall-retention-threshold = 70` — overall percent below which `high_overall_loss` fires.

### Automatic Flags

The skill sets these flags in `qc_summary.json` and `report.md`:

| Flag | Trigger | Action for researcher |
|------|---------|----------------------|
| `cutadapt_failed` | Cutadapt returned a non-zero exit status on this sample | Sample is excluded from downstream stats. Inspect `04_cutadapt_log.txt` and decide whether to re-run just this sample or exclude. |
| `extreme_drop` | Sample loses more than the threshold at any single stage on either R1 or R2 | Investigate — primer mismatch, low library quality, or contamination. |
| `low_read_count` | Sample retains fewer than the threshold on either R1 or R2 after primer trimming | Consider excluding — insufficient depth for reliable ASV inference. |
| `high_overall_loss` | Sample retains less than the threshold overall on either R1 or R2 | Investigate — cumulative quality issues. |

Either-side logic means a flag fires if R1 or R2 crosses the threshold — R2-specific problems (common at the 3' end on MiSeq 2×300) are visible even when the pair total looks fine. Individual-sample flags are informational; the 100%-data-loss backstop is separate and aborts only on run-level configuration errors.

## Example Queries

- "Run 16S QC on the FASTQ files in /path/to/raw with 341F/806R primers"
- "Trim primers and remove Ns from my amplicon data before DADA2"
- "Preprocess my V4 microbiome run — reads are in /path/to/raw"
- "Check whether my amplicon data has the right primer orientation before running the pipeline"
- "Show me a demo run so I can see what the outputs look like"

## Example Output

Captured from a real `--demo` invocation. Reproducible: `Rscript amplicon_qc.R --demo --output /tmp/demo`.

```
  claw-amplicon-qc v0.2.2
  Raw folder:     /path/to/tests/fixtures
  Output folder:  /tmp/demo
  Fwd primer:     GTGYCAGCMGCCGCGGTAA
  Rev primer:     GGACTACNVGGGTWTCTAAT
  Min length:     200

Detected naming pattern: Illumina default (SAMPLE_R1_..., SAMPLE_R2_...)
Discovered 1 sample pairs (paired by sample name).

  Preflight — primer orientation check
  Reads sampled (across 1 samples): 500
  R1 starting with forward primer: 494 (98.8%)
  R1 starting with reverse primer: 0 (0.0%)
  Orientation: consistent forward-oriented. OK.

  Stage 1/5 — Baseline seqkit stats on raw reads
  Total raw reads: 1,000

  Stage 2/5 — Removing reads containing N bases
  maxN threshold:        0
  PhiX removal:          ON
  Quality trimming:      OFF (deferred to downstream DADA2 skill)
  Minimum length filter: OFF (--min-length applies at Stage 4 only)
Read in 500 paired-sequences, output 497 (99.4%) filtered paired-sequences.

  Stage 3/5 — seqkit stats on N-filtered reads
  Total reads after N removal: 994

  Stage 4/5 — Primer trimming with Cutadapt
  Fwd: GTGYCAGCMGCCGCGGTAA   Fwd RC: TTACCGCGGCKGCTGRCAC
  Rev: GGACTACNVGGGTWTCTAAT   Rev RC: ATTAGAWACCCBNGTAGTCC
  Min length after trimming: 200 bp
  [1/1] demo

  Stage 5/5 — seqkit stats on primer-trimmed reads
  Total reads after primer trimming: 980

  Retention analysis + anomaly flagging
  Samples processed successfully:  1
  Samples failed (cutadapt):       0
  Samples flagged:                 1
  Flagged:                         demo

  claw-amplicon-qc — complete
  Samples processed:  1
  Samples flagged:    1
  Runtime:            1.3 s
```

Excerpt from the resulting `report.md`:

```markdown
# claw-amplicon-qc — QC Report

> **Disclaimer:** ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.

## Summary
- Samples processed successfully: **1**
- Samples failed (cutadapt): **0**
- Samples flagged: **1**
```

## Output Structure

```
output_folder/
├── report.md                       # Human-readable QC report (includes ClawBio disclaimer)
├── qc_summary.json                 # Machine-readable structured summary
├── 01_raw_stats.txt                # seqkit stats on raw reads
├── 02_filtN_stats.txt              # seqkit stats after N removal
├── 03_trimmed_stats.txt            # seqkit stats after primer trimming
├── 04_cutadapt_log.txt             # Per-sample Cutadapt log (with sample headers)
├── filtN/                          # N-filtered FASTQ files
│   ├── {sample}_R1_001.fastq.gz
│   └── {sample}_R2_001.fastq.gz
└── cutadapt_trimmed/               # Primer-trimmed FASTQ files
    ├── {sample}_R1_001.fastq.gz
    └── {sample}_R2_001.fastq.gz
```

## Dependencies

Install via conda from the bundled `environment.yml`:

```bash
conda env create -f environment.yml
conda activate amplicon-qc
```

Or manually:

```bash
conda create -n amplicon-qc -c conda-forge -c bioconda \
    r-base=4.4 bioconductor-dada2 bioconductor-shortread \
    bioconductor-biostrings r-optparse r-jsonlite \
    cutadapt seqkit
```

**Runtime:** R ≥ 4.4, Bioconductor (DADA2 for `filterAndTrim`, ShortRead + Biostrings for the preflight), CRAN (optparse for CLI, jsonlite for JSON output), plus binaries `cutadapt` (Stage 4) and `seqkit` (Stages 1, 3, 5).

## Gotchas

**Pre-primer-trimmed data will abort at the pre-flight.** If the sequencing facility already stripped primers before delivery, the pre-flight orientation check will report `primers_not_detected` and stop. This is intentional — the pipeline exists to *do* primer trimming; if there's nothing to trim, this is the wrong tool. Go directly to the downstream DADA2 skill.

**Extraction blanks trigger `low_read_count`, correctly.** Blanks are supposed to have almost nothing in them. The default 1000-read floor will fire on them. Not a bug; it means the flag logic works. Either accept the flags on blanks, lower `--low-count-threshold`, or use a metadata scheme to exclude blanks before running.

**Spaces in output paths are safe internally, but shells may still stumble.** The script `shQuote()`s all paths before passing to `system2()`, so `/mnt/d/Research Data/` works fine when invoked directly. If you're wrapping the call in a shell script, quote the path there too.

**Mixed-orientation libraries abort by default.** Some legitimate library preparations (some ONT amplicon protocols, older 454-derived workflows) produce reads where ~50% of R1 starts with the forward primer and ~50% starts with the reverse. The pre-flight aborts to prevent silent 50% data loss. Use `--allow-mixed-orientation` to proceed if you understand the trade-off.

## Safety

- **Local-first.** No data upload without explicit user consent. All processing runs on the invoking machine.
- **Disclaimer.** Every generated `report.md` includes the ClawBio disclaimer: *ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.*
- **No hallucinated science.** All outputs (read counts, retention percentages, flags) are directly measurable from FASTQ contents. No taxonomic or diversity claims are made anywhere.
- **Fail loud.** Configuration errors, missing tools, mispaired files, wrong primers, and 100% data loss all abort with actionable messages rather than produce a misleading report.

## Agent Boundary

The agent (LLM) dispatches and explains. The skill (R script) executes. The agent must NOT:

- Modify flag thresholds without explicit user request.
- Reclassify flagged samples as unflagged in downstream analysis.
- Proceed to DADA2 denoising without human review of the quality profiles the downstream skill will produce.
- Alter primer sequences the user supplied — always confirm changes with the user first.
- Overrule a pre-flight abort by silently adding `--allow-mixed-orientation` — the abort is a decision point that requires user awareness.

## Integration with Bio Orchestrator

**Trigger conditions.** The orchestrator routes here when:

- File extension `.fastq.gz` (or `.fq.gz`, `.fastq`, `.fq`) with paired-end R1/R2 naming
- Keywords from `metadata.openclaw.trigger_keywords` in the frontmatter

**Chaining partners.**

- **Upstream:** none. This is the earliest preprocessing skill in the amplicon chain.
- **Downstream:** the forthcoming DADA2 quality-filtering skill will consume `cutadapt_trimmed/` (primer-trimmed FASTQ pairs) plus `qc_summary.json` (per-sample flags and retention) and continue with quality profile review, `truncLen` selection, error learning, denoising, and paired-end merging.

Chain-ready outputs: `qc_summary.json` (structured, includes `preflight.primer_orientation`, `totals`, per-sample flags with nested R1/R2/pair counts) and `cutadapt_trimmed/` (the actual downstream input for DADA2).

## Maintenance

- **Review cadence:** on any Cutadapt or DADA2 major release. Verify `--pair-filter` default hasn't changed in Cutadapt; verify `filterAndTrim` parameter defaults haven't shifted in DADA2.
- **Staleness signals:** new primer conventions (dual-index barcoding artifacts, ONT amplicon protocols in Illumina-style workflows), sequencing platform shifts (Illumina NovaSeq X changes), changes to the astrobiomike tutorial dataset that would invalidate the bundled fixture.
- **Deprecation:** when the downstream DADA2 skill can consume outputs from a more integrated pipeline seamlessly, archive this skill to `skills/_deprecated/` with a note pointing at the successor.

## Citations

- [DADA2](https://doi.org/10.1038/nmeth.3869) — Callahan et al. (2016), *Nature Methods* 13:581–583; single-nucleotide-resolution amplicon denoising, provides `filterAndTrim` used at Stage 2.
- [Cutadapt](https://doi.org/10.14806/ej.17.1.200) — Martin (2011), *EMBnet.journal* 17(1):10–12; primer/adapter trimming, used at Stage 4.
- [seqkit](https://doi.org/10.1371/journal.pone.0163962) — Shen et al. (2016), *PLoS ONE* 11(10):e0163962; fast FASTQ statistics, used at Stages 1, 3, 5.

## License

MIT — see LICENSE file at the repository root.