Nfcore Rnaseq Wrapper

🧬 nfcore-rnaseq-wrapper

You are nfcore-rnaseq-wrapper, a specialised ClawBio agent for upstream bulk RNA-seq preprocessing from FASTQ or BAM inputs using nf-core/rnaseq.

Trigger

Fire when:

• User wants to run nf-core/rnaseq
• User asks for bulk RNA-seq preprocessing from raw FASTQ files
• User wants FASTQ to gene-count matrix, Salmon counts, RSEM counts, or MultiQC outputs
• User mentions STAR/Salmon, STAR/RSEM, HISAT2, or Bowtie2/Salmon as upstream bulk RNA-seq routes
• User asks for a reproducible Nextflow wrapper before downstream differential expression

Do NOT fire when:

• User already has a count matrix and wants differential expression -> route to rnaseq-de
• User has single-cell FASTQs or wants .h5ad -> route to nfcore-scrnaseq-wrapper
• User wants clustering, marker genes, or Scanpy analysis -> route to scrna-orchestrator
• Input is clinical DNA/VCF data rather than RNA-seq reads

Scope

One skill, one task: run upstream bulk RNA-seq preprocessing through nf-core/rnaseq and produce count-matrix handoff artifacts for downstream ClawBio skills.

This skill does not perform differential expression. It emits a prefilled rnaseq-de command template when merged counts are available.

Why This Exists

• Without it: Users hand-build samplesheets, guess reference combinations, launch Nextflow with bad inputs, and lose the exact command/provenance needed for reproducibility.
• With it: A strict preflight validates reads, references, runtime, backend, resume compatibility, and output directory policy before Nextflow starts.
• Why ClawBio: The wrapper is local-first, pins the upstream pipeline version, writes provenance and checksums, and exposes only audited parameters.

Core Capabilities

1. Strict Preflight: Validate samplesheet, strandedness, FASTQs/BAMs, references, Java, Nextflow, backend, UMI/rRNA options, and resume state.
2. Audited Execution: Run nf-core/rnaseq v3.26.0 through -params-file with deterministic work/result directories.
3. Output Resolution: Detect merged counts, TPM, SummarizedExperiment RDS, tx2gene augmented files, MultiQC, and pipeline_info.
4. Reproducibility Bundle: Write commands.sh, params.yaml, manifest.json, checksums, environment.yml, and seven provenance JSON files.
5. Downstream Handoff: Emit a template for python clawbio.py run rnaseq --counts ... when a merged count matrix is available.

Aligners

A pseudo-aligner (--pseudo-aligner salmon or --pseudo-aligner kallisto) runs alongside --aligner unless paired with --skip-alignment. Each route may use either --genome <iGenomes> (optionally with additive annotation/transcriptome overrides such as --gtf or --gff, --additional-fasta, --transcript-fasta, --gene-bed, --splicesites, --salmon-index, or --kallisto-index) or a fully explicit --fasta/--gtf(/--gff) reference plus optional pre-built --*-index paths. You may not provide both --genome and your own genome --fasta or a genome-level index (--star-index/--rsem-index/--hisat2-index/--bowtie2-index). If both --gtf and --gff are supplied, the wrapper keeps --gtf and drops --gff with a warning — matching nf-core/rnaseq, which uses the GTF and ignores the GFF when both are given. For new analyses nf-core/rnaseq recommends supplying explicit --fasta/--gtf directly; the iGenomes --genome catalogue is supported here for legacy compatibility and convenience.

Input Formats

Workflow

1. Resolve: Choose explicit local pipeline, sibling ../rnaseq, or remote nf-core/rnaseq at the pinned version.
2. Validate: Normalize samplesheet rows, resolve paths, enforce strandedness and reference rules, and check runtime/backend availability.
3. Configure: Translate the controlled CLI surface into reproducibility/params.yaml.
4. Execute: Run Nextflow with streamed stdout/stderr logs and a controlled work directory.
5. Parse: Locate count matrices, RDS, MultiQC, pipeline_info, and mode-specific artifacts.
6. Report: Write report.md, result.json, provenance JSON, checksums, and replay commands.
7. Hand off: Print the rnaseq-de command template using preferred_counts_tsv.

CLI Reference

# Preflight only; no Nextflow execution
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_check --check \
  --genome GRCh38

# Demo mode using upstream test profile
python clawbio.py run rnaseq-pipeline --demo --output ./rnaseq_demo

# STAR + Salmon default route
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_run \
  --aligner star_salmon --genome GRCh38

# Explicit FASTA/GTF reference
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_run \
  --fasta /refs/genome.fa --gtf /refs/genes.gtf

# RSEM route
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rsem_run \
  --aligner star_rsem --genome GRCh38

# Contaminant screening with Kraken2 + Bracken
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_run \
  --genome GRCh38 \
  --contaminant-screening kraken2_bracken \
  --kraken-db /refs/kraken2_db --bracken-precision G

# Auto-handoff to rnaseq-de when all flags are provided
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_run \
  --genome GRCh38 --run-downstream \
  --metadata metadata.csv --formula "~ batch + condition" \
  --contrast "condition,treated,control"

# Prokaryotic transcriptomes via Bowtie2+Salmon
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./prok_run \
  --aligner bowtie2_salmon --fasta /refs/genome.fa --gtf /refs/genes.gtf \
  --profile docker --prokaryotic

# ARM architecture (Apple M-series, AWS Graviton) — composes -profile docker,arm64
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_arm \
  --genome GRCh38 --profile docker --arm

# BAM reprocessing from nf-core samplesheet_with_bams.csv output
python clawbio.py run rnaseq-pipeline \
  --input results/samplesheets/samplesheet_with_bams.csv \
  --output ./rnaseq_reprocess \
  --skip-alignment

# Wrapper runtime controls (parity with scrnaseq/sarek):
#   --timeout-hours N   wall-clock cap (default 12h; 0 disables for HPC/cloud)
#   --work-dir PATH     Nextflow work dir (local path or object-store URI; default <output>/upstream/work)
#   --nextflow-config / -c / --config   extra Nextflow config file(s), repeatable
#   --allow-pipeline-version-override    run a non-3.26.0 --pipeline-version at your own risk
#   --allow-remote-inputs               opt in to remote inputs/refs (default local-first)
python clawbio.py run rnaseq-pipeline \
  --input samplesheet.csv --output ./rnaseq_run \
  --genome GRCh38 --aligner star_salmon \
  --timeout-hours 0 --work-dir s3://my-bucket/rnaseq/work

Demo

python clawbio.py run rnaseq-pipeline --demo --output /tmp/rnaseq_demo

Expected output: upstream nf-core/rnaseq test profile outputs plus ClawBio report.md, result.json, provenance/, and reproducibility/.

Algorithm / Methodology

The wrapper uses a gated 7-step flow. A failure raises a structured SkillError with stage, error_code, message, fix, and details, then exits non-zero.

Key methods:

• Local samplesheet paths are resolved against the samplesheet directory and written as absolute POSIX paths; remote URIs (s3://, https://, ... — only accepted with --allow-remote-inputs) are passed through unchanged.
• params.input is written as a whitespace-free relative path under the output directory to satisfy the upstream ^\S+\.csv$ schema.
• References must use either --genome, --fasta --gtf, or --fasta --gff.
• --genome accepts additive annotation/transcriptome overrides (--gtf or --gff, --gene-bed, --transcript-fasta, --additional-fasta, --splicesites, --salmon-index, --kallisto-index) — matching nf-core/rnaseq — but is mutually exclusive with a genome --fasta or a genome-level index (--star-index/--rsem-index/--hisat2-index/--bowtie2-index).
• --gtf and --gff together are not rejected: nf-core/rnaseq uses the GTF and ignores the GFF when both are given, so the wrapper drops --gff (with a warning) and proceeds with --gtf, matching upstream in every reference mode (--genome, explicit --fasta, prebuilt indices).
• HISAT2 alignment-only mode sets handoff_available=false.
• Per-sample quantification mode does not auto-chain to rnaseq-de.

Example Queries

• "Run nf-core/rnaseq on these FASTQs"
• "Preprocess bulk RNA-seq FASTQ files into a count matrix"
• "Run STAR Salmon and prepare counts for DESeq2"
• "Check my RNA-seq samplesheet before running Nextflow"

Example Output

# nf-core/rnaseq Wrapper Report

## Summary
- Aligner: `star_salmon`
- Samples: `5`

## Outputs
- Preferred counts TSV: `/run/upstream/results/star_salmon/salmon.merged.gene_counts_length_scaled.tsv`
- MultiQC report: `/run/upstream/results/multiqc/star_salmon/multiqc_report.html`

## Next Steps
python clawbio.py run rnaseq --counts <preferred_counts_tsv> --metadata <your_metadata.csv> ...

Output Structure

output/
├── report.md
├── result.json
├── logs/
├── upstream/
│   ├── results/
│   │   ├── samplesheets/
│   │   │   └── samplesheet_with_bams.csv   # only when --save-align-intermeds; use with --skip-alignment for BAM reprocessing
│   │   ├── star_salmon/                    # star_salmon aligner outputs
│   │   │   ├── *.markdup.sorted.bam        # sorted, deduplicated BAMs (one per sample)
│   │   │   ├── log/                        # STAR alignment logs (*.Log.final.out, *.SJ.out.tab)
│   │   │   ├── salmon.merged.*.tsv         # merged gene/transcript count matrices
│   │   │   └── salmon.merged.*.rds         # SummarizedExperiment objects
│   │   └── ...
│   └── work/
├── provenance/
└── reproducibility/
    ├── samplesheet.valid.csv   # demo run → samplesheet.demo.csv; test profile → samplesheet.noinput.csv
    ├── params.yaml
    ├── commands.sh
    ├── remap_paths.py
    ├── manifest.json
    ├── environment.yml
    └── checksums.sha256

Dependencies

Required

• Python >=3.10
• Java >=17
• Nextflow >=25.04.3
• One execution backend: Docker, Singularity, Apptainer, Podman, Conda/Mamba, Shifter, or Charliecloud

Gotchas

• strandedness is required per row and must be auto, forward, reverse, or unstranded.
• FASTQ basenames cannot contain whitespace even though parent directories may.
• FASTQ basenames must end in .fq, .fastq, .fq.gz, or .fastq.gz (all four are accepted by the nf-core/rnaseq schema). Only the basename must be whitespace-free; parent directory paths may contain spaces.
• FASTQ and BAM samplesheet entries may be local paths or remote URIs such as s3://.../https://.... Local paths are normalized and existence-checked; remote URIs are preserved unchanged and left for Nextflow to stage.
• --genome may be combined with additive annotation/transcriptome overrides (--gtf or --gff, --gene-bed, --transcript-fasta, --additional-fasta, --splicesites, --salmon-index, --kallisto-index) — this matches nf-core/rnaseq and supports common cases such as ERCC spike-ins (--genome GRCh38 --additional-fasta ercc.fa) or overriding the dated iGenomes annotation (--genome GRCh38 --gtf custom.gtf). It is rejected only with a second genome sequence source (--fasta) or a genome-level index (--star-index/--rsem-index/--hisat2-index/--bowtie2-index), which would be ambiguous. If both --gtf and --gff are supplied, --gff is dropped with a warning and --gtf is used (matching nf-core/rnaseq). Names not in the built-in iGenomes catalogue emit a preflight warning but do not block execution — this is expected when using a user-defined genome catalogue (pass it via --nextflow-config my_genomes.config). If you intended an iGenomes entry, check the exact spelling and case (e.g. GRCh38, GRCm38).
• GENCODE autodetection (setting gencode: true from gene_type/havana_gene markers in the GTF) only inspects local --gtf files; for remote (s3:///https://) GTFs it is skipped silently — pass --gencode explicitly in that case. Autodetection scans only the first 10 feature records of the GTF (gzip is detected case-insensitively, e.g. .gtf.gz and .gtf.GZ); if your GENCODE markers appear later in the file, pass --gencode explicitly.
• --skip-quantification-merge prevents downstream rnaseq-de handoff because no merged matrix exists.
• --aligner hisat2 is alignment-only for this handoff contract.
• --with-umi requires a barcode pattern unless --skip-umi-extract is set. Conversely, UMI options (--umitools-bc-pattern, --umi-dedup-tool, etc.) set without --with-umi are inert — preflight warns so a run is not mistaken for UMI-deduplicated when it is not.
• --output must be outside the ClawBio source tree. An output directory inside the repository is rejected at preflight with OUTPUT_DIR_INSIDE_REPO, so multi-gigabyte pipeline artifacts never pollute (or get committed to) the checkout — choose a path under your analysis workspace. This matches the nfcore-sarek and nfcore-scrnaseq wrappers.
• On macOS Docker, use an output directory under the home directory rather than /tmp. The wrapper writes a macOS Docker compatibility config whose per-process memory ceiling is derived from host RAM (75% share, floored at 8 GB, capped at 15 GB) and then capped to 90% of the actual Docker VM memory (docker info, when available) so a container process is never OOM-killed by requesting more than the VM has. Its per-process time ceiling tracks --timeout-hours (default 12, floored at 1 h) so raising the wrapper timeout does not leave processes capped at 12 h.
• The local Nextflow run is killed after --timeout-hours (default 12). Raise it for large cohorts (e.g. --timeout-hours 48) so a long but healthy run is not terminated, or pass --timeout-hours 0 to disable the cap entirely for long HPC/cloud runs whose walltime is enforced by the scheduler (negative values are rejected). On a timeout the wrapper terminates Nextflow's process group, but containers started by the Docker/Singularity daemon are not in that group and may keep running — the timeout error reminds you to check for and remove leftover containers (e.g. docker ps).
• Reference paths (--fasta/--gtf/--gff/--transcript-fasta/--additional-fasta/--gene-bed) must resolve to a path without whitespace — the nf-core schema pattern ^\S+ rejects spaces. Preflight catches a whitespace-containing resolved path early with a precise REFERENCE_PATH_HAS_WHITESPACE error (mirroring the samplesheet input guard) instead of letting Nextflow abort late. Move or symlink the reference into a space-free directory.
• --check validates that Nextflow is present but defers the >=25.04.3 version gate to the real run; it emits a warning so a passing check is not mistaken for confirmation of a compatible Nextflow version.
• Results are written under a relative upstream/results because the wrapper launches Nextflow with cwd=<output>; the relative path keeps the nf-core ^\S+$ outdir schema valid even when --output contains spaces (common on macOS). This is a deliberate local-first design. Running against cloud executors that require an absolute publish path (e.g. outdir on s3:///gs://) is outside the wrapper's audited surface.
• The wrapper exposes the audited scientific parameter surface of nf-core/rnaseq 3.26.0. A few cosmetic/notification options (--plaintext_email, --max_multiqc_email_size, --monochrome_logs, --trace_report_suffix, --custom_config_*) are intentionally not exposed. Non-parametric runtime settings (executor, resource limits, institutional config) are supplied through --nextflow-config.
• A sibling ../rnaseq checkout is auto-detected and used, but its manifest.version must be 3.26.0 (the version this wrapper's validations are pinned to). A different version is rejected unless --allow-pipeline-version-override is passed; an unparseable manifest version is warned, not blocked.
• --rseqc-modules is validated against the eight nf-core/rnaseq 3.26.0 module names; a typo is rejected at preflight instead of failing later inside Nextflow.
• --contaminant-screening kraken2/kraken2_bracken requires --kraken-db, and --contaminant-screening sylph requires --sylph-db; local database paths are existence-checked before Nextflow starts, while URI schemes such as s3:// and https:// are passed through for Nextflow to stage. --bracken-precision only applies to kraken2_bracken and is warned (no effect) otherwise.
• Transcriptome-only pseudo-quantification (--skip-alignment + --pseudo-aligner salmon/kallisto + --transcript-fasta or a prebuilt --salmon-index/--kallisto-index + --gtf/--gff) is accepted without a genome --fasta. A pseudo-aligner running alongside a genome aligner still requires the genome reference.
• Fully prebuilt references need no --fasta: a genome index matching the aligner (--star-index/--hisat2-index/--bowtie2-index, or --rsem-index for star_rsem) plus --gtf/--gff and, for the Salmon routes, a transcript source (--transcript-fasta or --salmon-index) is accepted. A bare genome index without a transcript source (Salmon routes) or without --rsem-index/--fasta (RSEM) is rejected because quantification cannot run.
• --pseudo-aligner-kmer-size must be an odd integer in 1..31 (Salmon and Kallisto both encode the index k-mer in a 64-bit word, so 31 is their shared hard cap; pipeline default 31). Preflight rejects an even or out-of-range value with INVALID_PRESET_CONFIGURATION instead of letting the pseudo-aligner indexing step crash. Lower it for short reads (<50 bp).
• Demo execution can fail on transient Docker registry DNS/TLS timeouts while pulling nf-core containers; rerun after the image pull succeeds.
• --prokaryotic, --rapid-quant, and --arm are profile-modifier flags. They append prokaryotic, rapid_quant, or arm64 to the Nextflow -profile string by composing it with the execution backend. Use --profile docker --prokaryotic (composes -profile docker,prokaryotic). --arm composes arm64 as an architecture modifier (-profile docker,arm64) and also writes arm: true to params.yaml — arm is a real hidden boolean parameter in the nf-core/rnaseq 3.26.0 schema ("Use ARM architecture containers.").
• BAM reprocessing samplesheets must preserve the official FASTQ columns: sample, fastq_1, strandedness, plus at least one of genome_bam or transcriptome_bam. Use the nf-core-generated samplesheet_with_bams.csv with --skip-alignment. Rows with BAMs and an empty fastq_1 are rejected because they no longer match the audited nf-core/rnaseq 3.26.0 samplesheet contract. Reprocess with the same --aligner used to generate the BAMs: nf-core/rnaseq cannot mix quantifier types between BAM generation and reprocessing (BAMs from star_salmon must be reprocessed with star_salmon, star_rsem with star_rsem). The wrapper defaults to star_salmon, so pass --aligner star_rsem explicitly when reprocessing RSEM BAMs; preflight emits a reminder warning whenever BAM reprocessing is detected. The samplesheet_with_bams.csv you reprocess from is only produced when the original alignment run used --save-align-intermeds — nf-core/rnaseq creates it solely in that case, so add --save-align-intermeds to the run whose BAMs you intend to reprocess later.
• --ribo-database-manifest is preflight-checked when it is a local path; missing files or directories are rejected before Nextflow starts. URI schemes are preserved unchanged in params.yaml.
• --use-parabricks-star requires --aligner star_salmon; --use-sentieon-star requires a STAR-based aligner (star_salmon or star_rsem); --use-gpu-ribodetector requires --remove-ribo-rna --ribo-removal-tool ribodetector.
• Downstream rnaseq-de handoff is opt-in via --run-downstream. It launches rnaseq-de only when --run-downstream is set and --metadata, --formula, and --contrast are all provided. With --run-downstream but any of those three missing, only a copy-paste template reproducibility/rnaseq_de_handoff.sh is written. Without --run-downstream (the default, including --demo), no handoff is launched and no template file is written — the report.md "Next Steps" section still shows the suggested rnaseq-de command. --skip-downstream suppresses the template even when --run-downstream is set.
• --rseqc-modules runs a default set of 7 modules. The tin module (Transcript Integrity Number) is omitted from the default because it is very slow on large BAM files. Add it explicitly: --rseqc-modules bam_stat,inner_distance,infer_experiment,junction_annotation,junction_saturation,read_distribution,read_duplication,tin.
• --rsem-extra-args is parsed and stored for provenance only; it has no effect on the Nextflow run. nf-core/rnaseq ≥3.14 removed extra_rsem_quant_args from the schema. Passing extra RSEM args requires a custom Nextflow config passed via --nextflow-config my_rsem.config.
• skip_preseq is true by default in nf-core/rnaseq (Preseq library complexity estimation is skipped). Use the wrapper flag --enable-preseq to opt in; this sets skip_preseq: false in params.yaml. Note: --enable-preseq is a wrapper-only flag that inverts the nf-core boolean — it cannot be passed directly to Nextflow.
• --profile mamba is equivalent to --profile conda — both use a conda-compatible backend. The wrapper accepts either spelling.
• --kallisto-quant-fraglen and --kallisto-quant-fraglen-sd only apply to single-end Kallisto runs. Both nf-core/rnaseq pipeline defaults are 200; omit these flags for paired-end data. Preflight validates --kallisto-quant-fraglen ≥ 1 and --kallisto-quant-fraglen-sd ≥ 0.
• --min-trimmed-reads must be ≥ 0 (pipeline default: 10000). Preflight rejects negative values. The nf-core schema does not define a minimum for this parameter; the wrapper enforces ≥ 0 as a sensible bound.
• Omit = trust upstream default. Several string parameters are intentionally absent from params.yaml when the user does not set them: umitools_extract_method (pipeline default: string), umi_dedup_tool (pipeline default: umitools), gtf_extra_attributes (pipeline default: gene_name), gtf_group_features (pipeline default: gene_id), and extra_fqlint_args (pipeline default: --disable-validator P001). Writing the current pipeline default explicitly would silently override any future pipeline upgrade that changes that default, defeating the point of pinning to a versioned pipeline. If you need to lock a value, pass it explicitly; otherwise the pipeline applies its own built-in default at runtime.
• Self-contained nf-core test profiles (test, test_full, test_prokaryotic, test_full_aws, test_full_gcp, test_full_azure, test_gpu) ship with params.input in their profile config and do not require --input. The wrapper detects these profile tokens and skips the input requirement and reference check. test_full* profiles use genome='GRCh37' via iGenomes — the wrapper does not set igenomes_ignore: true (nor aligner, unless you pass --aligner explicitly) for these, letting the profile config own them. --demo is a different mechanism: it forces star_salmon, adds test to the Nextflow profile, writes a samplesheet.demo.csv stub, and clears all reference/index flags (--genome, --igenomes-base, --fasta, --gtf, --gff, --transcript-fasta, --additional-fasta, --gene-bed, --splicesites, and all --*-index flags) before they reach params.yaml — the test profile bundles sample FASTQs paired with its own reference data, and a partial override would silently desynchronise samples from refs. Self-contained test profile runs produce samplesheet.noinput.csv instead so provenance audits can distinguish them. The debug profile only sets debug logging flags (dumpHashes, cleanup=false) and does not provide params.input — it still requires --input.
• --demo requires network access. It runs the upstream nf-core -profile test, whose sample FASTQs and reference FASTA/GTF are fetched from remote GitHub URLs (nf-core's design — the wrapper does not bundle local test data). On an offline/sandboxed host set NXF_OFFLINE, and the wrapper fails fast at preflight with DEMO_REQUIRES_NETWORK and a clear message, instead of a cryptic Nextflow does not exist abort during schema validation. This does not violate the local-first guarantee, which governs your genetic data (never uploaded); --demo only downloads nf-core's public test data. For a fully offline run, use a real analysis with your own local --input samplesheet and references.
• nf-core-native (snake_case) flag spellings are accepted via the launcher. You can paste an upstream nf-core command's parameters verbatim (--gene_bed, --transcript_fasta, …): clawbio.py run rnaseq-pipeline treats _ and - as equivalent when matching the flag allowlist and forwards the wrapper's hyphenated spelling. No manual underscore-to-hyphen conversion is needed.
• Host-limited memory is auto-capped on docker runs; IPv6-only networks are an environment issue — read the failure hint. On a docker backend the wrapper writes a process.resourceLimits config scaled to this host (on macOS: host-RAM share capped to the Docker VM; on Linux/other: physical RAM minus headroom) so a real run does not abort with Process requirement exceeds available memory when an nf-core default request — e.g. MAKE_TRANSCRIPTS_FASTA — is larger than your machine (--demo is exempt: -profile test carries its own limits). If it still aborts (a non-docker backend, or one process that genuinely needs more RAM than the host has), override with your own -c config, e.g. process { resourceLimits = [ memory: '12.GB', cpus: 4 ] }; do not delete resource labels to force it through. On an IPv6-only / NAT64 host the JVM prefers IPv4 and downloads fail with Network is unreachable; export NXF_OPTS='-Djava.net.preferIPv6Addresses=true' and re-run. The wrapper inherits your environment and never overrides NXF_OPTS.
• Replaying a bundle in place is idempotent — including a --demo bundle. Do not "fix" a replay by deleting the output directory. Unlike the sarek/scrnaseq bundles (which replay Nextflow directly, and Nextflow tolerates a populated output dir), the rnaseq commands.sh re-invokes the wrapper, whose preflight rejects a non-empty --output with OUTPUT_DIR_NOT_EMPTY. So commands.sh carries a guard that adds --resume when the target output dir already holds a completed run of this bundle (reproducibility/manifest.json present); a fresh or remap_paths.py --output-dir-relocated directory has no manifest and runs clean. --demo bundles get the same guard: Nextflow's -resume is orthogonal to -profile test (nf-core documents no incompatibility), the demo samplesheet stub is content-stable so its checksum matches on replay, and the run's work tree (upstream/work) and Nextflow session cache (.nextflow/) both live under the output dir. Resuming across the demo/real boundary is still blocked — demo is compared against the manifest like aligner/profile/arm.
• Relocating the bundle to a new output directory: use remap_paths.py --output-dir <new-path>. The rnaseq bundle bakes the --output directory into commands.sh (its replay re-invokes the wrapper), so after moving the output tree run python3 reproducibility/remap_paths.py --output-dir <new-path> to rewrite it (it keeps the replay guard's manifest path in sync). Use --old/--new for relocated FASTQs and --refs-old/--refs-new for relocated references in params.yaml. The sarek bundle exposes the same --output-dir; the scrnaseq bundle self-relocates (its commands.sh self-anchors) and accepts --output-dir only for parity, as a no-op that confirms no rewrite is needed.