Open Skills Logo
Open Skills

pacsomatic

用于从 BAM 输入构建 nf-core/pacsomatic 匹配肿瘤-正常工作流的操作员工具包。当用户需要验证运行输入、生成符合 pacsomatic 的 samplesheet、准备可复现的 Nextflow 启动工件、在本地运行或提交到调度器（LSF/Slurm/PBS/SGE），以及对执行失败进行分诊排查时，请使用此能力。触发条件包括：请求运行 pacsomatic、准备启动命令/脚本、执行干运行检查，或排查流水线启动及调度器提交错误。

作者

@K-Dense-AI

分类

开发工具

安装

热度:0

下载并解压到你的 skills 目录

复制命令，发送给智能体自动安装：

下载并安装这个技能 https://openskills.cc/api/download?slug=k-dense-ai-skills-pacsomatic&locale=zh&source=copy
name:pacsomaticdescription: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.license:MITmetadata:[object Object]

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

  • Always collect required run inputs first.

  • Always route through scripts/run_pacsomatic.py for validation and artifact generation.

  • Default to --dry-run when the user asks for checks/validation only.

  • Use --run only when the user asks to execute/submit.

  • For scheduler modes, include executor-specific resource arguments and return detected job ID when available.

  • 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

  • Validate identity and input constraints.

  • Validate required local paths (BAM, optional PBI, optional FASTA).

  • Resolve runtime and dependency checks.

  • Build samplesheet and generated params YAML.

  • Generate launch script for selected executor.

  • If --dry-run and not --run, stop after artifact generation.

  • If --run, execute locally or submit to scheduler.

  • 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 -v

    References

  • references/agent-playbook.md

  • references/config-and-output.md

  • references/pacsomatic_guide.md

  • scripts/run_pacsomatic.py