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pacsomatic

pacsomatic

Operator toolkit for nf-core/pacsomatic matched tumor-normal workflows from BAM inputs. Use this skill when the user needs to validate run inputs, generate pacsomatic-compliant samplesheets, prepare reproducible Nextflow launch artifacts, run locally or submit to schedulers (LSF/Slurm/PBS/SGE), and triage execution failures. Triggers on requests to run pacsomatic, prepare launch commands/scripts, perform dry-run checks, or troubleshoot pipeline startup and scheduler submission errors.

pacsomatic

Overview

This skill provides a reproducible execution workflow for nf-core/pacsomatic, centered on a single helper entrypoint that handles validation, artifact generation, and optional execution.

Primary entrypoint:

  • scripts/run_pacsomatic.py

The helper script:

  • validates required identifiers, files, reference mode, and runtime prerequisites
  • writes a pacsomatic-compatible samplesheet (patient,sample,status,bam,pbi)
  • generates a params YAML and launch script for reproducible reruns
  • supports dry-run validation and run/submit execution paths

Use this skill as the default path for pacsomatic operations. Do not bypass it with manually assembled nextflow run nf-core/pacsomatic commands unless the user explicitly asks for manual command construction.

When to Use This Skill

Invoke this skill when the user asks to:

  • run matched tumor-normal analysis from BAM files
  • generate or fix pacsomatic samplesheet and launch artifacts
  • execute locally or submit to schedulers (LSF/Slurm/PBS/SGE)
  • perform dry-run validation before execution
  • troubleshoot launch failures or summarize run outputs

Do not use this skill for:

  • deep biological interpretation beyond run-level sanity checks
  • editing pipeline internals unless explicitly requested

Typical trigger phrases:

  • "run nf-core/pacsomatic for this tumor-normal pair"
  • "prepare pacsomatic samplesheet and launch script"
  • "do a dry run first and tell me what is missing"
  • "submit pacsomatic to slurm/lsf and return the job id"
  • "why did pacsomatic submission fail"

Routing and Execution Rules

  1. Always collect required run inputs first.
  2. Always route through scripts/run_pacsomatic.py for validation and artifact generation.
  3. Default to --dry-run when the user asks for checks/validation only.
  4. Use --run only when the user asks to execute/submit.
  5. For scheduler modes, include executor-specific resource arguments and return detected job ID when available.
  6. If execution fails, report first failure point and next triage target (.nextflow.log, pipeline_info, failing task logs).

Inputs Required

Required:

  • tumor BAM path
  • normal BAM path
  • patient ID
  • tumor sample ID
  • normal sample ID
  • output directory
  • exactly one reference mode: --fasta or --genome

Optional:

  • profile, resources, scheduler account/queue
  • pipeline version (-r)
  • params file, resume/report/dag flags
  • --dry-run and/or --run

Workflow

  1. Validate identity and input constraints.
  2. Validate required local paths (BAM, optional PBI, optional FASTA).
  3. Resolve runtime and dependency checks.
  4. Build samplesheet and generated params YAML.
  5. Generate launch script for selected executor.
  6. If --dry-run and not --run, stop after artifact generation.
  7. If --run, execute locally or submit to scheduler.
  8. Return command/script path, validation status, and job ID (if detected).

Agent Response Contract

Every response after invocation should include:

  • exact command used or generated script path
  • confirmation that validation checks ran
  • run type (dry-run vs run)
  • scheduler job ID when available
  • one concrete next step for validation/triage

Quick Start

Dry run:

python scripts/run_pacsomatic.py \
  --tumor-bam /path/to/tumor.bam \
  --normal-bam /path/to/normal.bam \
  --patient-id P001 \
  --tumor-sample-id P001_T \
  --normal-sample-id P001_N \
  --outdir /path/to/output \
  --genome GRCh38 \
  --profile singularity,sanger \
  --dry-run

Scheduler execution example (Slurm):

python scripts/run_pacsomatic.py \
  --tumor-bam /path/to/tumor.bam \
  --normal-bam /path/to/normal.bam \
  --patient-id P001 \
  --tumor-sample-id P001_T \
  --normal-sample-id P001_N \
  --outdir /path/to/output \
  --genome GRCh38 \
  --profile singularity,sanger \
  --executor slurm \
  --queue compute \
  --project my_account \
  --cpus 16 \
  --memory-gb 64 \
  --walltime 48:00 \
  --run

Configuration

Use config.yaml as the baseline for profile/executor/runtime defaults. Override at invocation time when user requirements differ.

Testing

Run unit tests from skill root:

python -m unittest discover -s tests/pacsomatic -v

References

  • references/agent-playbook.md
  • references/config-and-output.md
  • references/pacsomatic_guide.md
  • scripts/run_pacsomatic.py

安装中心

可直接安装到 9 个框架(另有 Cursor / Windsurf 需转换为 rules 格式)。悬停可查看各框架的技能目录。

方式一 · 复制提示词(推荐)

粘贴给你的 Claude Code,它会自己完成下载和安装(安装文件直接取自原始仓库)

请帮我安装技能「pacsomatic」:
1. 从原始仓库下载技能文件:https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/pacsomatic/SKILL.md(GitHub 上的 SKILL.md 原始文件)
2. 保存为 ~/.claude/skills/pacsomatic/SKILL.md(目录不存在则创建)
3. 确认文件存在后,告诉我安装结果

方式二 · 命令行安装

npx CLI 跨平台可用(自动检测本机 Agent);PowerShell 方式无需安装任何东西

npx ailine-skills add pacsomatic
New-Item -ItemType Directory -Force "$HOME\.claude\skills\pacsomatic" | Out-Null; curl.exe -fsSL "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/pacsomatic/SKILL.md" -o "$HOME\.claude\skills\pacsomatic\SKILL.md"

方式三 · 前往原始仓库

第三方技能不由本站分发安装文件,请从原始仓库获取(上方命令/提示词已直连原始文件)