Skip to content

/pipeline-wgbs

Execute ENCODE Whole Genome Bisulfite Sequencing (WGBS) pipeline from FASTQ to methylation calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing WGBS/bisulfite-seq data, calling methylation levels, generating bedMethyl

From plugin
2994 skills7 agents10 commands
shell
$ npx -y skills add ammawla/encode-toolkit --skill pipeline-wgbs --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/pipeline-wgbs
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Execute ENCODE Whole Genome Bisulfite Sequencing (WGBS) pipeline from FASTQ to methylation calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing WGBS/bisulfite-seq data, calling methylation levels, generating bedMethyl

SKILL.md

pipeline-wgbs.SKILL.md
name: pipeline-wgbs
description: "Execute ENCODE Whole Genome Bisulfite Sequencing (WGBS) pipeline from FASTQ to methylation calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing WGBS/bisulfite-seq data, calling methylation levels, generating bedMethyl files. Trigger on: WGBS pipeline, bisulfite sequencing, methylation calling, DNA methylation pipeline, bismark, bwa-meth, bedMethyl."

ENCODE WGBS Pipeline: FASTQ to Methylation Calls

When to Use

  • User wants to run a WGBS/bisulfite sequencing pipeline from FASTQ to methylation calls
  • User asks about "WGBS pipeline", "bisulfite sequencing", "methylation calling", "Bismark", or "bedMethyl"
  • User needs to process whole-genome bisulfite sequencing data following ENCODE standards
  • Example queries: "process my WGBS FASTQs", "call methylation levels from bisulfite-seq", "run Bismark on my WGBS data"

Execute the ENCODE DNA methylation pipeline for Whole Genome Bisulfite Sequencing data, producing per-CpG methylation levels in bedMethyl format.

Pipeline Overview

FASTQ -> Trim adapters -> Bismark align -> Deduplicate -> MethylDackel extract -> bedMethyl
  |           |               |                |                |                    |
  QC      Trim Galore    Bismark/bwa-meth   Picard         Per-CpG calls      Final output

ENCODE Repository

  • **GitHub**: `ENCODE-DCC/dna-me-pipeline`
  • **Container**: `encodedcc/dna-me-pipeline`
  • **WDL**: Available for Cromwell execution
  • **This skill**: Nextflow DSL2 reimplementation for portability

Core Tools and Versions

| Tool | Version | Purpose | Citation | |------|---------|---------|----------| | Trim Galore | 0.6.10 | Adapter + quality trimming (bisulfite-aware) | Krueger (Babraham) | | Bismark | 0.24.2 | Bisulfite-aware alignment + methylation | Krueger & Andrews 2011 | | bwa-meth | 0.2.7 | Alternative bisulfite aligner (faster) | Pedersen 2014 | | MethylDackel | 0.6.1 | Methylation extraction from BAM | Ryan (GitHub) | | Picard | 3.1.1 | Duplicate marking | Broad Institute | | samtools | 1.19 | BAM operations | Li et al. 2009 | | FastQC | 0.12.1 | Read quality assessment | Andrews (Babraham) | | MultiQC | 1.21 | Aggregated QC reporting | Ewels et al. 2016 |

Key Literature

1. **Krueger & Andrews 2011** - "Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications" (Bioinformatics, ~4,000 citations) DOI: 10.1093/bioinformatics/btr167

2. **Lister et al. 2009** - "Human DNA methylomes at base resolution show widespread epigenomic differences" (Nature, ~5,000 citations) DOI: 10.1038/nature08514

3. **Schultz et al. 2015** - "Human body epigenome maps reveal noncanonical DNA methylation variation" (Nature, ~1,500 citations) DOI: 10.1038/nature14248

4. **Pedersen et al. 2014** - "Fast and accurate alignment of long bisulfite-seq reads" arXiv:1401.1129 (bwa-meth)

5. **Amemiya et al. 2019** - "The ENCODE Blacklist" (Scientific Reports, ~1,372 citations) DOI: 10.1038/s41598-019-45839-z

Execution

Quick Start (Local)

nextflow run main.nf \
    -profile local \
    --reads '/data/fastq/*_R{1,2}.fastq.gz' \
    --genome_dir '/ref/bismark_index' \
    --outdir results/ \
    -resume

SLURM HPC

nextflow run main.nf \
    -profile slurm \
    --reads '/data/fastq/*_R{1,2}.fastq.gz' \
    --genome_dir '/ref/bismark_index' \
    --outdir results/ \
    -resume

Cloud (GCP / AWS)

nextflow run main.nf \
    -profile gcp \
    --reads 'gs://bucket/fastq/*_R{1,2}.fastq.gz' \
    --genome_dir 'gs://bucket/ref/bismark_index' \
    --outdir 'gs://bucket/results/' \
    -resume

Resource Requirements

| Step | CPUs | RAM | Time (30x human) | |------|------|-----|-------------------| | Trim Galore | 4 | 4 GB | 1-2 hours | | Bismark align | 8 | 48 GB | 8-16 hours | | Deduplication | 2 | 16 GB | 1-2 hours | | MethylDackel | 4 | 8 GB | 1-2 hours | | **Total** | **8** | **48 GB** | **12-24 hours** |

Pipeline Parameters

| Parameter | Default | Description | |-----------|---------|-------------| | `--reads` | required | Glob pattern to paired FASTQ files | | `--genome_dir` | required | Path to Bismark genome index directory | | `--outdir` | `./results` | Output directory | | `--aligner` | `bismark` | Aligner: `bismark` or `bwameth` | | `--min_coverage` | `5` | Minimum coverage for CpG reporting | | `--no_overlap` | `true` | Remove overlapping PE reads (avoid double-counting) | | `--lambda_genome` | `null` | Lambda genome index for conversion rate QC | | `--skip_dedup` | `false` | Skip deduplication (for RRBS data) |

Output Files

results/
  fastqc/                    # Raw read quality
  trim_galore/               # Trimmed reads + reports
  bismark/
    alignments/              # Sorted, deduplicated BAMs
    dedup_reports/           # Duplication metrics
    methylation/             # bedMethyl files (primary output)
      {sample}.CpG.bedMethyl.gz
      {sample}.CHG.bedMethyl.gz   # Non-CpG contexts
      {sample}.CHH.bedMethyl.gz
    conversion_rate/         # Lambda/pUC19 conversion QC
  coverage/
    {sample}.coverage_stats.txt
  multiqc/
    multiqc_report.html

bedMethyl Format

The primary output is per-CpG methylation in bedMethyl format:

chr1  10468  10470  .  1000  +  10468  10470  0,0,0  12  83.3

Columns: chr, start, end, name, score, strand, thickStart, thickEnd, color, coverage, methylation_percentage

QC Thresholds (ENCODE Standards)

| Metric | Pass | Warning | Fail | |--------|------|---------|------| | Bisulfite conversion rate | ≥98% | 95-98% | <95% | | CpG coverage (genome-wide) | >10x | 5-10x | <5x | | Mapping rate | >70% | 50-70% | <50% | | Duplication rate | <30% | 30-50% | >50% | | CpG sites covered (>=5x) | >80% | 60-80% | <60% | | Lambda spike-in conversion | ≥98% | 95-98% | <95% |

Critical Pitfalls

RRBS vs WGBS

RRBS (Reduced Representation) uses MspI

Read more
Read it on GitHub ↗

Showing the first part of this file.

Ships withencode-toolkit

Search ENCODE, cross-reference 14 databases, run 7 analysis pipelines, and generate publication-ready methods — all from natural language in Claude Code.

Get the whole plugin, auto-invoked
Stats
29
Stars
0
Views
5
Forks
Active
Maintenance
Python
Language
AGPL-3.0
License
8d ago
Last commit
4mo ago
Created

Repo: ammawla/encode-toolkit

Other skills on encode-toolkit.