Skip to main content

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.

来源信息

仓库
synthetic-sciences/openscience
最近来源活动
2026年9月16日 06:26
检测到的 SKILL.md 语言
英语
星标
4,251
Forks
532

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

检查来源文件

决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

文件资源管理器
7 个文件

正在显示 SKILL.md

SKILL.md
来源说明 · 只读预览
name
pacsomatic
description
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.
category
biology
license
MIT
metadata
{"upstream":"K-Dense-AI/scientific-agent-skills","upstream-url":"https://github.com/K-Dense-AI/scientific-agent-skills","upstream-path":"skills/pacsomatic","upstream-license":"MIT","upstream-relationship":"derived","adapted-by":"Synthetic Sciences","version":"1.2","skill-author":"Beifang Niu","contributors":"Haidong, Wenchao","upstream-pipeline":"https://github.com/nf-core/pacsomatic"}
# 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: ```bash 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): ```bash 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: ```bash 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`
在 GitHub 查看