pyflow-ChIPseq CLAUDE.md

pyflow-ChIPseq: Repository Structure and Overview

Analysis Date: 2025-12-26 Branch: modernize-2025 (based on pairend) Purpose: Documentation for understanding and modernizing the ChIP-seq pipeline

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Table of Contents

1. Repository Purpose
2. Directory Structure
3. Key Components
4. Technology Stack
5. Workflow Overview
6. Configuration System
7. Modernization Priorities

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Repository Purpose

pyflow-ChIPseq is a Snakemake-based bioinformatics pipeline for processing and analyzing Chromatin Immunoprecipitation Sequencing (ChIP-seq) data. It automates the complete workflow from raw sequencing reads to peak calling and chromatin state analysis.

Key Features

• Processes both public (GEO/SRA) and in-house ChIP-seq data
• Supports single-end and paired-end sequencing reads
• Handles both short (<70bp) and long (>70bp) reads
• Automated quality control and reporting
• Advanced downstream analysis (super-enhancers, chromatin states)
• Cluster deployment support (SLURM/DRMAA)

Publication

This pipeline was published in the Journal of Visualized Experiments (JOVE): "An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues"

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Directory Structure

pyflow-ChIPseq/
├── Snakefile                    # Main workflow definition (21,957 bytes)
├── config.yaml                  # Pipeline configuration and parameters
├── cluster.json                 # Cluster job submission resource specs
├── samples.json                 # Sample metadata (auto-generated)
│
├── sample2json.py               # Metadata converter (TSV → JSON)
├── sbatch_cluster.py            # SLURM job submission wrapper
├── pyflow-ChIPseq.sh            # Main execution script (SLURM)
├── pyflow-drmaa-ChIPseq.sh      # DRMAA-based execution (LSF)
├── jobscript.sh                 # Job script template
│
├── scripts/
│   └── sraDownload.R            # SRA data downloader
│
├── SRR.txt                      # Sample metadata template (GEO data)
├── meta.txt                     # Custom metadata template (in-house data)
│
├── README.md                    # User documentation
├── LICENSE                      # MIT License
├── rulegraph.png                # Workflow DAG visualization
├── GEO_rulegraph.png            # Alternative workflow visualization
└── TCGA_related files           # TCGA barcode documentation

### Output Directories (Created During Execution)

- `00log/` - Log files for all rules
- `01seq/` - Merged FASTQ files
- `02fqc/` - FastQC quality control reports
- `03aln/` - Aligned BAM files and indices
- `04aln_downsample/` - Downsampled BAM files
- `05phantompeakqual/` - Phantom peak quality metrics
- `06bigwig_inputSubtract/` - Input-subtracted bigWig tracks
- `07bigwig/` - RPKM-normalized bigWig tracks
- `08peak_macs1/` - MACS1 peak calls
- `09peak_macs2/` - MACS2 peak calls
- `10multiQC/` - MultiQC quality summary report
- `11superEnhancer/` - Super enhancer calls (ROSE)
- `12bed/` - BED format files
- `13chromHMM/` - Chromatin state predictions