OverviewHistoryStatsSecurity
npx skills add ...
Documentation
SKILL.md
npx skills add anthropics/life-sciences --skill nextflow-development
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.
npx skills add anthropics/life-sciences --skill nextflow-development
Run nf-core bioinformatics pipelines on local or public sequencing data.
Target users: Bench scientists and researchers without specialized bioinformatics training who need to run large-scale omics analyses—differential expression, variant calling, or chromatin accessibility analysis.
Skip this step if user has local FASTQ files.
For public datasets, fetch from GEO/SRA first. See references/geo-sra-acquisition.md for the full workflow.
Quick start:
DECISION POINT: After fetching study info, confirm with user:
Then continue to Step 1.
Run first. Pipeline will fail without passing environment.
All critical checks must pass. If any fail, provide fix instructions:
| Problem | Fix |
|---|---|
| Not installed | Install from https://docs.docker.com/get-docker/ |
| Permission denied | sudo usermod -aG docker $USER then re-login |
| Daemon not running | sudo systemctl start docker |
| Problem | Fix |
|---|---|
| Not installed | curl -s https://get.nextflow.io | bash && mv nextflow ~/bin/ |
| Version < 23.04 | nextflow self-update |
| Problem | Fix |
|---|---|
| Not installed / < 11 | sudo apt install openjdk-11-jdk |
Do not proceed until all checks pass. For HPC/Singularity, see references/troubleshooting.md.
DECISION POINT: Confirm with user before proceeding.
| Data Type | Pipeline | Version | Goal |
|---|---|---|---|
| RNA-seq | rnaseq | 3.22.2 | Gene expression |
| WGS/WES | sarek | 3.7.1 | Variant calling |
| ATAC-seq | atacseq | 2.1.2 | Chromatin accessibility |
Auto-detect from data:
For pipeline-specific details:
Validates environment with small data. MUST pass before real data.
| Pipeline | Command |
|---|---|
| rnaseq | nextflow run nf-core/rnaseq -r 3.22.2 -profile test,docker --outdir test_rnaseq |
| sarek | nextflow run nf-core/sarek -r 3.7.1 -profile test,docker --outdir test_sarek |
| atacseq | nextflow run nf-core/atacseq -r 2.1.2 -profile test,docker --outdir test_atacseq |
Verify:
If test fails, see references/troubleshooting.md.
The script:
For sarek: Script prompts for tumor/normal status if not auto-detected.
rnaseq:
sarek:
atacseq:
Common genomes: GRCh38 (human), GRCh37 (legacy), GRCm39 (mouse), R64-1-1 (yeast), BDGP6 (fly)
DECISION POINT: Confirm with user:
Key flags:
-r: Pin version-profile docker: Use Docker (or singularity for HPC)--genome: iGenomes key-resume: Continue from checkpointResource limits (if needed):
rnaseq:
results/star_salmon/salmon.merged.gene_counts.tsv - Gene countsresults/star_salmon/salmon.merged.gene_tpm.tsv - TPM valuessarek:
results/variant_calling/*/ - VCF filesresults/preprocessing/recalibrated/ - BAM filesatacseq:
results/macs2/narrowPeak/ - Peak callsresults/bwa/mergedLibrary/bigwig/ - Coverage tracksFor common exit codes and fixes, see references/troubleshooting.md.
This skill is provided as a prototype example demonstrating how to integrate nf-core bioinformatics pipelines into Claude Code for automated analysis workflows. The current implementation supports three pipelines (rnaseq, sarek, and atacseq), serving as a foundation that enables the community to expand support to the full set of nf-core pipelines.
It is intended for educational and research purposes and should not be considered production-ready without appropriate validation for your specific use case. Users are responsible for ensuring their computing environment meets pipeline requirements and for verifying analysis results.
Anthropic does not guarantee the accuracy of bioinformatics outputs, and users should follow standard practices for validating computational analyses. This integration is not officially endorsed by or affiliated with the nf-core community.
When publishing results, cite the appropriate pipeline. Citations are available in each nf-core repository's CITATIONS.md file (e.g., https://github.com/nf-core/rnaseq/blob/3.22.2/CITATIONS.md).
python scripts/check_environment.pypython scripts/detect_data_type.py /path/to/datanextflow run nf-core/<pipeline> -r <version> -profile test,docker --outdir test_outputls test_output/multiqc/multiqc_report.html
grep "Pipeline completed successfully" .nextflow.logpython scripts/generate_samplesheet.py /path/to/data <pipeline> -o samplesheet.csvpython scripts/generate_samplesheet.py --validate samplesheet.csv <pipeline>sample,fastq_1,fastq_2,strandedness
SAMPLE1,/abs/path/R1.fq.gz,/abs/path/R2.fq.gz,autopatient,sample,lane,fastq_1,fastq_2,status
patient1,tumor,L001,/abs/path/tumor_R1.fq.gz,/abs/path/tumor_R2.fq.gz,1
patient1,normal,L001,/abs/path/normal_R1.fq.gz,/abs/path/normal_R2.fq.gz,0sample,fastq_1,fastq_2,replicate
CONTROL,/abs/path/ctrl_R1.fq.gz,/abs/path/ctrl_R2.fq.gz,1python scripts/manage_genomes.py check <genome>
# If not installed:
python scripts/manage_genomes.py download <genome>nextflow run nf-core/<pipeline> \
-r <version> \
-profile docker \
--input samplesheet.csv \
--outdir results \
--genome <genome> \
-resume--max_cpus 8 --max_memory '32.GB' --max_time '24.h'ls results/multiqc/multiqc_report.html
grep "Pipeline completed successfully" .nextflow.lognextflow run nf-core/<pipeline> -resume