pacsomatic

pacsomatic - nf-core Tumor-Normal Pairing Analysis Run Assistant

Skill Overview

pacsomatic is a dedicated run assistant for the nf-core/pacsomatic workflow. It helps you start tumor-normal paired analysis from BAM files, automatically handling input validation, sample sheet generation, workflow startup, and scheduler submission.

Use Cases

1. Tumor-Normal Paired BAM Analysis

If you have BAM files for both tumor and normal samples and need to run nf-core/pacsomatic for somatic variant calling, this skill can verify the completeness and correctness of the input files, generate a sample sheet that meets pacsomatic formatting requirements (patient,sample,status,bam,pbi), and prepare a reproducible Nextflow startup configuration.

2. Local Execution or Scheduler Submission

Supports running the analysis directly on a local server, or submitting it to common job schedulers such as LSF, Slurm, PBS, and SGE. The skill automatically generates the appropriate submission scripts and resource configuration parameters based on the target scheduler, returning the job ID for tracking execution status.

3. Pre-Run Validation and Troubleshooting

Performs a dry-run check before the正式 execution to confirm that required parameters such as the reference genome, BAM file paths, and sample IDs are present and correct. If the workflow fails to start, it helps identify the first failure point, checks .nextflow.log, pipeline_info, and failed task logs, and provides concrete remediation suggestions.

Core Features

1. Input Validation and Sample Sheet Generation

Automatically validates required run inputs: tumor BAM path, normal BAM path, patient ID, tumor sample ID, normal sample ID, output directory, and reference mode (--fasta or --genome). Optional validations include PBI files and local FASTA files. After validation, it generates a pacsomatic-compatible sample sheet and a parameters YAML file.

2. Reproducible Startup Script Generation

Generates standardized startup scripts for local runs or scheduler execution, including all run parameters, profile configuration, resource limits, and scheduler-specific settings. Once saved, the script can be used for fully identical reproducible runs or as a template for fine-tuning.

3. Scheduler Integration and Execution Monitoring

Supports four major schedulers: LSF, Slurm, PBS, and SGE. Automatically adapts queue, account, CPU, memory, and walltime parameters for each scheduler. After execution, it returns detected job IDs to facilitate monitoring via scheduler commands. If execution fails, it reports the failure point and the next troubleshooting target.

Frequently Asked Questions

How do I run nf-core pacsomatic from BAM files?

Use the scripts/run_pacsomatic.py script by providing the tumor and normal BAM file paths, sample IDs, and output directory. For example:

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

Which schedulers does pacsomatic support?

Supports four major job scheduling systems: LSF, Slurm, PBS, and SGE. Use the --executor parameter to specify the scheduler type, and submit jobs with parameters such as queue (--queue), project account (--project), CPU (--cpus), memory (--memory-gb), and runtime (--walltime).

How can I troubleshoot pacsomatic startup failures?

First, check .nextflow.log to locate the first failure point, and inspect the pipeline_info directory to understand the workflow configuration. For specific task failures, check the corresponding .command.out, .command.err, and .exit files. Common causes include: incorrect BAM file paths, reference genome mismatch, insufficient scheduler resources, or an incorrectly formatted sample sheet. The skill automatically identifies the failure type and provides remediation suggestions.