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"datePublished": "2025-11-20T09:31:39+00:00",
"description": "<h1>\n <picture>\n <source media=\"(prefers-color-scheme: dark)\" srcset=\"docs/images/nf-core-longraredisease_logo_dark.png\">\n <img alt=\"nf-core/longraredisease\" src=\"docs/images/nf-core-longraredisease_logo_light.png\">\n </picture>\n</h1>\n\n[](https://github.com/codespaces/new/nf-core/longraredisease)\n[](https://github.com/nf-core/longraredisease/actions/workflows/nf-test.yml)\n[](https://github.com/nf-core/longraredisease/actions/workflows/linting.yml)[](https://nf-co.re/longraredisease/results)[](https://doi.org/10.5281/zenodo.XXXXXXX)\n[](https://www.nf-test.com)\n\n[](https://www.nextflow.io/)\n[](https://github.com/nf-core/tools/releases/tag/3.5.1)\n[](https://docs.conda.io/en/latest/)\n[](https://www.docker.com/)\n[](https://sylabs.io/docs/)\n[](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/longraredisease)\n\n[](https://nfcore.slack.com/channels/longraredisease)\n[](https://twitter.com/nf_core)\n[](https://mstdn.science/@nf_core)\n[](https://www.youtube.com/c/nf-core)\n\n---\n\n## Introduction\n\n**nf-core/longraredisease** is a specialized bioinformatics pipeline for **structural variant (SV) detection and clinical interpretation** from long-read sequencing data (Oxford Nanopore and PacBio). Designed for rare disease diagnostics, it delivers high-confidence variant discovery through multi-caller consensus, family-based analysis, and phenotype-driven prioritization.\n\n\n\n### \ud83c\udfaf **Primary Focus: Structural Variant Detection**\n\nThe pipeline excels at identifying and interpreting structural variants through:\n\n- **Multi-caller SV consensus** - Sniffles, CuteSV, SVIM with JASMINE merging\n- **Phase-aware calling** - Haplotype-resolved SV detection using LongPhase\n- **Family analysis** - Trio-based joint calling and de novo variant detection\n- **Clinical annotation** - AnnotSV with disease database integration\n- **Phenotype prioritization** - SVANNA-based ranking using HPO terms\n\n### \ud83d\udcca **Analysis Capabilities**\n\n**Core SV Analysis (Always Enabled):**\n\n- \u2705 **Structural Variants** - Multi-caller detection (DEL, INS, DUP, INV, BND)\n- \u2705 **Phasing** - Long-range haplotyping with LongPhase\n- \u2705 **Quality Control** - Comprehensive QC with NanoPlot, mosdepth, MultiQC\n\n**Optional Analyses:**\n\n- \ud83e\uddec **Single Nucleotide Variants** - Clair3 or DeepVariant (enable with `--snv true`)\n- \ud83d\udcc8 **Copy Number Variants** - Spectre or HiFiCNV (enable with `--cnv true`)\n- \ud83d\udd01 **Short Tandem Repeats** - Straglr genotyping (enable with `--str true`)\n- \ud83e\uddea **DNA Methylation** - Modkit extraction for ONT (enable with `--methyl true`)\n\n---\n\n## Requirements\n\n### Software\n\n- **Nextflow** \u226525.04.6 (DSL2)\n- **Container engine:** Docker, Singularity/Apptainer, or Podman\n- **Java** \u226517 (required by Nextflow)\n\n### Recommended Hardware\n\n| Analysis Type | CPU Cores | Memory | Storage |\n| --------------------- | --------- | -------- | ------- |\n| **Single WGS sample** | 8-16 | 32-64 GB | 100 GB |\n\n**Notes:**\n\n- Coverage recommendations: \u226510x for accurate SV calling, \u226530x for high-confidence trio analysis\n- Storage includes space for input data, intermediate files, and results\n- Adjust `--max_cpus` and `--max_memory` parameters based on available resources\n\n---\n\n## Quick Start\n\n### 1. Install Nextflow\n\n```bash\n# Install Nextflow (\u226525.04.6)\ncurl -s https://get.nextflow.io | bash\nsudo mv nextflow /usr/local/bin/\n\n# Verify installation\nnextflow -version\n```\n\n### 2. Test the Pipeline\n\n```bash\n# Run with test data\nnextflow run nf-core/longraredisease \\\n -profile test,docker \\\n --outdir test_results\n```\n\n### 3. Run with the Longraredisease Test Data\n\n**Minimal SV-focused run:**\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir results \\\n --fasta reference.fasta \\\n --sequencing_platform ont \\\n -profile docker\n```\n\n**With family analysis and phenotype prioritization:**\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir results \\\n --fasta reference.fasta \\\n --sequencing_platform ont \\\n --trio_analysis true \\\n --run_svanna true \\\n --svanna_db /path/to/svanna_db \\\n -profile docker\n```\n\nSee [docs/usage.md](docs/usage.md) for complete examples and parameter details.\n\n---\n\n## Input Requirements\n\n### Required Inputs\n\n| Parameter | Description | Format | Example |\n| ----------------------- | -------------------------------- | --------------------------- | ----------------- |\n| `--input` | Samplesheet with sample metadata | CSV | `samplesheet.csv` |\n| `--outdir` | Output directory | Path | `./results` |\n| `--fasta` | Reference genome FASTA | `.fasta`/`.fa` | `GRCh38.fasta` |\n| `--sequencing_platform` | Platform type | `ont` or `pacbio` or `hifi` | `ont` |\n\n### Samplesheet Format\n\nThe input samplesheet is a CSV file with the following columns:\n\n**Minimal format (single samples):**\n\n```csv\nsample,bam,bai\nsample1,/path/to/sample1.bam,/path/to/sample1.bam.bai\nsample2,/path/to/sample2.bam,/path/to/sample2.bam.bai\n```\n\n**Family analysis format (trios):**\n\n```csv\nsample,bam,bai,family,paternal_id,maternal_id,sex,phenotype,hpo_terms\nproband,proband.bam,proband.bam.bai,family1,father,mother,1,affected,\"HP:0001250,HP:0002066\"\nfather,father.bam,father.bam.bai,family1,0,0,1,unaffected,\nmother,mother.bam,mother.bam.bai,family1,0,0,2,unaffected,\n```\n\n**Column descriptions:**\n\n- `sample` - Unique sample identifier\n- `bam` - Path to aligned BAM file\n- `bai` - Path to BAM index file\n- `family` - Family identifier (for trio analysis)\n- `paternal_id` - Father's sample ID (or `0` if not in study)\n- `maternal_id` - Mother's sample ID (or `0` if not in study)\n- `sex` - `1` = male, `2` = female, `0` = unknown\n- `phenotype` - `affected` or `unaffected`\n- `hpo_terms` - Comma-separated HPO terms (e.g., `HP:0001250,HP:0002066`)\n\n### Optional Inputs\n\n| Parameter | Description | Required For |\n| -------------- | ----------------------- | ------------------------ |\n| `--bed` | Target regions BED file | Targeted sequencing |\n| `--annotsv_db` | AnnotSV database path | SV annotation |\n| `--svanna_db` | SVANNA database path | Phenotype prioritization |\n| `--str_bed` | STR loci BED file | STR analysis |\n\n---\n\n## Key Parameters\n\n### Core Analysis Toggles\n\n**Structural variant analysis is always enabled.** Optional analyses:\n\n| Parameter | Description | Default |\n| ---------- | --------------------------------------------- | ------- |\n| `--snv` | Enable SNV calling (Clair3/DeepVariant) | `false` |\n| `--cnv` | Enable CNV detection (Spectre) | `false` |\n| `--str` | Enable STR genotyping (Straglr) | `false` |\n| `--methyl` | Enable methylation calling (Modkit, ONT only) | `false` |\n\n### SV Detection Parameters\n\n| Parameter | Description | Default |\n| -------------------- | ----------------------------------------- | ------- |\n| `--run_cutesv` | Enable CuteSV caller | `true` |\n| `--run_svim` | Enable SVIM caller (recommended for BNDs) | `false` |\n| `--haplotag_bam` | Haplotag BAM for phase-aware SV calling | `true` |\n| `--min_sv_size` | Minimum SV size to report (bp) | `30` |\n| `--min_read_support` | Minimum supporting reads | `auto` |\n\n### Family Analysis Parameters\n\n| Parameter | Description | Default |\n| ----------------- | -------------------------------------- | ------- |\n| `--trio_analysis` | Enable trio/family-based calling | `false` |\n| `--run_svanna` | Enable phenotype-driven prioritization | `false` |\n| `--svanna_db` | Path to SVANNA database | - |\n\n### Multi-caller Consensus Parameters\n\n| Parameter | Description | Default |\n| ----------------------- | ----------------------------------------- | ------- |\n| `--jasmine_max_dist` | Max distance for merging breakpoints (bp) | `1000` |\n| `--jasmine_min_support` | Min callers supporting merged variant | `2` |\n| `--jasmine_spec_reads` | Min supporting reads for consensus | `3` |\n\n### Platform-specific Settings\n\n| Parameter | Description | Options |\n| ----------------------- | ------------------------- | ------------------------------- |\n| `--sequencing_platform` | Sequencing platform | `ont`, `pacbio` |\n| `--preset` | Minimap2 alignment preset | `map-ont`, `map-hifi`, `map-pb` |\n| `--snv_caller` | SNV caller choice | `clair3`, `deepvariant` |\n\n---\n\n## Usage Examples\n\n### 1. Standard SV Analysis (Single Sample)\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n -profile docker\n```\n\n### 2. Comprehensive Analysis (SVs + SNVs + CNVs)\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform pacbio \\\n --snv true \\\n --cnv true \\\n --str true \\\n -profile singularity\n```\n\n### 3. Family Trio Analysis with Phenotype Prioritization\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input trio_samplesheet.csv \\\n --outdir family_results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n --trio_analysis true \\\n --run_svanna true \\\n --svanna_db /databases/svanna_data \\\n --annotsv_db /databases/AnnotSV \\\n -profile docker\n```\n\n### 4. High-Sensitivity SV Detection\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir sensitive_results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n --run_svim true \\\n --min_sv_size 20 \\\n --min_read_support 2 \\\n --jasmine_min_support 1 \\\n -profile docker\n```\n\n### 5. Targeted Sequencing with BED File\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --outdir targeted_results \\\n --fasta GRCh38.fasta \\\n --bed targets.bed \\\n --sequencing_platform ont \\\n -profile docker\n```\n\n---\n\n## Output Structure\n\n```\nresults/\n\u251c\u2500\u2500 pipeline_info/ # Pipeline execution reports\n\u2502 \u251c\u2500\u2500 execution_report.html # Resource usage timeline\n\u2502 \u251c\u2500\u2500 execution_timeline.html # Process execution graph\n\u2502 \u2514\u2500\u2500 multiqc_report.html # Comprehensive QC report\n\u2502\n\u251c\u2500\u2500 qc/ # Quality control metrics\n\u2502 \u251c\u2500\u2500 mosdepth/ # Coverage statistics per sample\n\u2502 \u251c\u2500\u2500 nanoplot/ # Read quality metrics (ONT)\n\u2502 \u2514\u2500\u2500 cramino/ # CRAM-based QC (optional)\n\u2502\n\u251c\u2500\u2500 structural_variants/ # \ud83c\udfaf PRIMARY OUTPUT: SV calls\n\u2502 \u251c\u2500\u2500 sniffles/ # Per-sample Sniffles VCFs\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.sniffles.vcf.gz\n\u2502 \u251c\u2500\u2500 cutesv/ # Per-sample CuteSV VCFs\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.cutesv.vcf.gz\n\u2502 \u251c\u2500\u2500 svim/ # Per-sample SVIM VCFs (if enabled)\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.svim.vcf.gz\n\u2502 \u251c\u2500\u2500 merged/ # Multi-caller consensus SVs\n\u2502 \u2502 \u251c\u2500\u2500 {sample}.jasmine.vcf.gz\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.survivor.vcf.gz\n\u2502 \u251c\u2500\u2500 annotated/ # AnnotSV annotations\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.annotated.tsv\n\u2502 \u2514\u2500\u2500 svanna/ # Phenotype-prioritized SVs\n\u2502 \u2514\u2500\u2500 {sample}.svanna.html\n\u2502\n\u251c\u2500\u2500 phasing/ # Haplotype-resolved results\n\u2502 \u251c\u2500\u2500 haplotagged_bams/ # Phase-tagged alignments\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.haplotagged.bam\n\u2502 \u251c\u2500\u2500 whatshap/ # Phasing statistics\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.phased.vcf.gz\n\u2502 \u2514\u2500\u2500 longphase/ # Alternative phasing\n\u2502 \u2514\u2500\u2500 {sample}.longphase.vcf.gz\n\u2502\n\u251c\u2500\u2500 snv_calls/ # SNVs (if --snv enabled)\n\u2502 \u251c\u2500\u2500 clair3/\n\u2502 \u2502 \u2514\u2500\u2500 {sample}.clair3.vcf.gz\n\u2502 \u2514\u2500\u2500 deepvariant/\n\u2502 \u2514\u2500\u2500 {sample}.deepvariant.vcf.gz\n\u2502\n\u251c\u2500\u2500 cnv_calls/ # CNVs (if --cnv enabled)\n\u2502 \u2514\u2500\u2500 spectre/\n\u2502 \u2514\u2500\u2500 {sample}.cnv.vcf.gz\n\u2502\n\u251c\u2500\u2500 str_calls/ # STRs (if --str enabled)\n\u2502 \u2514\u2500\u2500 straglr/\n\u2502 \u2514\u2500\u2500 {sample}.straglr.tsv\n\u2502\n\u2514\u2500\u2500 methylation/ # Methylation (if --methyl enabled, ONT only)\n \u2514\u2500\u2500 modkit/\n \u2514\u2500\u2500 {sample}.bedmethyl.gz\n```\n\n**Key output files:**\n\n- **Merged SVs**: `structural_variants/merged/{sample}.jasmine.vcf.gz` (high-confidence consensus)\n- **Annotated SVs**: `structural_variants/annotated/{sample}.annotated.tsv` (clinical interpretation)\n- **QC Report**: `pipeline_info/multiqc_report.html` (overall quality assessment)\n- **Phenotype-prioritized**: `structural_variants/svanna/{sample}.svanna.html` (ranked by phenotype match)\n\n---\n\n## Configuration Profiles\n\n**Available Profiles:**\n\n- test: Minimal test dataset\n- docker: Use Docker containers\n- singularity: Use Singularity containers\n\n**Custom Configuration**\n\n```bash\n// custom.config\nparams {\n max_cpus = 16\n max_memory = '64.GB'\n outdir = '/scratch/results'\n}\n\nprocess {\n withName: 'CLAIR3' {\n cpus = 8\n memory = '32.GB'\n }\n}\n```\n\nRun with:\n\n```bash\nnextflow run main.nf -c custom.config -profile docker\n```\n\n---\n\n## Family-Based Analysis\n\n### Trio/Family Configuration\n\nFor family-based SV analysis, provide pedigree information in your samplesheet:\n\n```csv\nsample,bam,bai,family,paternal_id,maternal_id,sex,phenotype,hpo_terms\nchild_001,child.bam,child.bam.bai,FAM001,father_001,mother_001,2,affected,\"HP:0001250,HP:0002066,HP:0001263\"\nfather_001,father.bam,father.bam.bai,FAM001,0,0,1,unaffected,\nmother_001,mother.bam,mother.bam.bai,FAM001,0,0,2,unaffected,\n```\n\n**Sex encoding:** `1` = male, `2` = female, `0` = unknown\n**Parental IDs:** Use `0` for founders (individuals with no parents in the study)\n\n### De Novo SV Detection\n\nEnable trio analysis to identify _de novo_ structural variants:\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input trio_samplesheet.csv \\\n --trio_analysis true \\\n --outdir trio_results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n -profile docker\n```\n\nThe pipeline will:\n\n1. \u2705 Call SVs in each family member independently\n2. \u2705 Merge calls using JASMINE with family-aware parameters\n3. \u2705 Identify variants present in child but absent in parents\n4. \u2705 Filter based on read support and quality metrics\n\n### Phenotype-Driven Prioritization (SVANNA)\n\nWhen HPO terms are provided, SVANNA ranks SVs by phenotype relevance:\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input trio_samplesheet.csv \\\n --trio_analysis true \\\n --run_svanna true \\\n --svanna_db /path/to/svanna/2302 \\\n --outdir prioritized_results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n -profile docker\n```\n\n**Required:** Download SVANNA database from [Monarch Initiative](https://github.com/TheJacksonLaboratory/SvAnna)\n\n**Output:** HTML report ranking SVs by:\n\n- Overlap with disease-associated genes\n- Regulatory impact predictions\n- Phenotype similarity scores\n- De novo status (if trio data available)\n\n### Annotation with AnnotSV\n\nEnable comprehensive SV annotation:\n\n```bash\nnextflow run nf-core/longraredisease \\\n --input samplesheet.csv \\\n --annotsv_db /path/to/AnnotSV_db \\\n --outdir annotated_results \\\n --fasta GRCh38.fasta \\\n --sequencing_platform ont \\\n -profile docker\n```\n\n**AnnotSV provides:**\n\n- Gene overlap and functional impact\n- ClinGen/ClinVar annotations\n- DGV/gnomAD population frequencies\n- Pathogenicity predictions (ACMG criteria)\n- Regulatory element disruption\n\n---\n\n## Troubleshooting\n\n### Common Issues\n\n#### 1. Low SV Detection Rate\n\n**Symptoms:** Fewer SVs than expected\n\n**Solutions:**\n\n```bash\n# Lower read support threshold\n--min_read_support 2\n\n# Reduce minimum SV size\n--min_sv_size 20\n\n# Enable SVIM for better breakend detection\n--run_svim true\n\n# Lower consensus requirement\n--jasmine_min_support 1\n```\n\n#### 2. High False Positive Rate\n\n**Symptoms:** Many low-quality SV calls\n\n**Solutions:**\n\n```bash\n# Increase read support\n--min_read_support 5\n\n# Require multiple caller agreement\n--jasmine_min_support 2\n\n# Increase minimum SV size\n--min_sv_size 50\n```\n\n#### 3. Memory Issues\n\n**Symptoms:** Process killed due to OOM\n\n**Solutions:**\n\n```bash\n# Increase max memory\n--max_memory 128.GB\n\n# Reduce parallel processes\n--max_cpus 16\n\n# Use chromosome-based parallelization (automatic)\n```\n\n#### 4. Missing De Novo Variants\n\n**Symptoms:** Expected _de novo_ variants not detected\n\n**Checklist:**\n\n- \u2705 Ensure `--trio_analysis true` is set\n- \u2705 Verify pedigree information in samplesheet\n- \u2705 Check read coverage in all samples (\u226530\u00d7)\n- \u2705 Review `structural_variants/merged/` for family calls\n- \u2705 Lower `--jasmine_min_support` if needed\n\n#### 5. SVANNA Database Issues\n\n**Symptoms:** SVANNA fails or produces no rankings\n\n**Solutions:**\n\n```bash\n# Verify database path and version\nls -lh /path/to/svanna/2302\n\n# Ensure HPO terms are valid (HP:XXXXXXX format)\n# Check samplesheet for proper HPO term formatting\n\n# Download latest SVANNA database:\nwget https://storage.googleapis.com/svanna-db/svanna-data-2302.tar.gz\ntar -xzf svanna-data-2302.tar.gz\n```\n\n### Performance Optimization\n\n**For large cohorts (>10 samples):**\n\n```bash\n# Enable resource-efficient mode\n--max_cpus 64\n--max_memory 256.GB\n\n# Use Singularity for better resource isolation\n-profile singularity\n\n# Enable work directory cleanup\n-resume -with-dag flowchart.html\n```\n\n**For whole genome sequencing:**\n\n- Expect 8-24 hours runtime (depending on coverage)\n- Allocate 64-128GB RAM per sample for SV calling\n- Use SSD storage for work directory (I/O intensive)\n\n---\n\n## Test Data\n\nThe pipeline includes test data for validation:\n\n- Location: assets/test_data/\n- Genome: Chromosome 22 subset\n- Samples: Simulated nanopore data\n- Runtime: ~10-15 minutes\n\n---\n\n## Getting Help\n\n**Debugging Failed Runs:**\n\n```bash\n# Check Nextflow log for detailed errors\nless .nextflow.log\n\n# Resume from last successful step\nnextflow run nf-core/longraredisease -resume\n\n# Enable debug mode for verbose output\nnextflow run nf-core/longraredisease --debug -profile docker\n```\n\n**Reporting Issues:**\n\nWhen reporting issues, please include:\n\n- Nextflow version (`nextflow -version`)\n- Command used to run the pipeline\n- Relevant error messages from `.nextflow.log`\n- Sample metadata (anonymized if sensitive)\n- System specifications (CPU, RAM, storage)\n\n---\n\n## Citation\n\nIf you use **nf-core/longraredisease** in your research, please cite:\n\n> **nf-core/longraredisease: A Nextflow pipeline for long-read sequencing analysis in rare disease research** > _Citation to be added upon publication_\n\nAdditionally, please cite the tools used in your analysis:\n\n**Core SV Tools:**\n\n- **Sniffles2:** Sedlazeck et al. (2018) _Nature Methods_\n- **CuteSV:** Jiang et al. (2020) _Genome Biology_\n- **JASMINE:** Kirsche et al. (2023) _Nature Methods_\n- **LongPhase:** Luo et al. (2023) _Nature Communications_\n- **AnnotSV:** Geoffroy et al. (2018) _Bioinformatics_\n\n**Optional Analysis Tools:**\n\n- **SVANNA:** Danis et al. (2022) _AJHG_\n- **Clair3:** Zheng et al. (2022) _Nature Computational Science_\n- **Spectre:** Suvakov et al. (2021) _Genome Research_\n- **Straglr:** Chin et al. (2023) _Genome Research_\n\n---\n\n## Contributing\n\nContributions are welcome! To contribute:\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/AmazingFeature`)\n3. Make your changes following [nf-core guidelines](https://nf-co.re/developers/guidelines)\n4. Test with `nextflow run . -profile test,docker`\n5. Commit your changes (`git commit -m 'Add AmazingFeature'`)\n6. Push to the branch (`git push origin feature/AmazingFeature`)\n7. Open a Pull Request\n\n**Please ensure:**\n\n- \u2705 Code follows nf-core style guidelines\n- \u2705 All tests pass successfully\n- \u2705 Documentation is updated accordingly\n- \u2705 Commit messages are descriptive\n\n---\n\n## License\n\nThis project is licensed under the MIT License \u2013 see the [LICENSE](LICENSE) file for details.\n\n---\n\n## Acknowledgments\n\nThis pipeline was developed with support from [institution/funding sources]. We thank the nf-core community for infrastructure and best practices, and all tool developers whose software makes this pipeline possible.\n\n---\n\n**Pipeline Version:** 1.0.0\n**Nextflow Version:** \u226525.04.6\n**Last Updated:** 2024\n",
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