/pipeline-dnaseseq

name: pipeline-dnaseseq
description: "Execute ENCODE DNase-seq pipeline from FASTQ to hotspots and footprints. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing DNase-seq data, calling DNase hypersensitive sites, performing footprinting analysis. Trigger on: DNase-seq pipeline, DNase hypersensitive, DHS, Hotspot2, footprinting, DNase I, chromatin accessibility DNase."

ENCODE DNase-seq Pipeline: FASTQ to Hotspots and Footprints

When to Use

• User wants to run a DNase-seq processing pipeline from FASTQ to hotspots and footprints
• User asks about "DNase-seq pipeline", "DNase hypersensitive sites", "Hotspot2", "footprinting", or "DHS"
• User needs to process DNase-seq data for chromatin accessibility and TF footprint analysis
• Example queries: "process my DNase-seq FASTQs", "call DNase hypersensitive sites", "run footprinting analysis on DNase-seq"

Execute the ENCODE DNase-seq pipeline for chromatin accessibility profiling, producing DNase hypersensitive sites (DHSs) via Hotspot2 and transcription factor footprints.

Pipeline Overview

FASTQ -> Trim -> BWA-MEM align -> Filter/dedup -> Hotspot2 -> DHS peaks
                                       |                        |
                                    Signal track         Footprinting (HINT)

ENCODE Repository

• **GitHub**: `ENCODE-DCC/dnase-seq-pipeline`
• **Container**: built from `scripts/Dockerfile` in this skill (`docker build -t encode-toolkit/pipeline-dnaseseq:1.0.0 scripts/`); override with `--container`
• **WDL**: Available for Cromwell execution
• **This skill**: Nextflow DSL2 reimplementation for portability

Core Tools and Versions

| Tool | Version | Purpose | Citation | |------|---------|---------|----------| | BWA-MEM | 0.7.18 | Alignment | Li & Durbin 2009 | | samtools | 1.19 | BAM operations | Li et al. 2009 | | Picard | 3.1.1 | Duplicate marking | Broad Institute | | Hotspot2 | 2.1.2 | DHS calling (ENCODE standard) | John et al. 2011 | | modwt | 1.0 | Wavelet smoothing used by Hotspot2 | Stam Lab | | bedtools | 2.31.0 | Genomic arithmetic | Quinlan & Hall 2010 | | BEDOPS | apt (Ubuntu 22.04) | `sort-bed` and `unstarch` for the Hotspot2 starch archives | Neph et al. 2012 | | HINT (RGT) | 1.0.2 | TF footprinting | Li et al. 2019 | | FastQC | 0.12.1 | Read quality | Andrews (Babraham) | | Trim Galore | 0.6.10 | Adapter and quality trimming | Krueger (Babraham) | | cutadapt | 4.6 | Adapter removal backend for Trim Galore | Martin 2011 | | MultiQC | 1.21 | Aggregated QC | Ewels et al. 2016 |

Key Literature

1. **John et al. 2011** - "Chromatin accessibility pre-determines glucocorticoid receptor binding patterns" (Nature Genetics, ~600 citations) DOI: 10.1038/ng.759

2. **Thurman et al. 2012** - "The accessible chromatin landscape of the human genome" (Nature, ~3,000 citations) DOI: 10.1038/nature11232

3. **Vierstra et al. 2020** - "Global reference mapping of human transcription factor footprints" (Nature, ~600 citations) DOI: 10.1038/s41586-020-2528-x

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

5. **Li et al. 2019** - "Identification of transcription factor binding sites using ATAC-seq" (Genome Biology) -- HINT-ATAC footprinting DOI: 10.1186/s13059-019-1642-2

Execution

Quick Start (Local)

nextflow run scripts/main.nf \
    -profile local \
    --reads '/data/fastq/*_R{1,2}.fastq.gz' \
    --bwa_index '/ref/bwa_index/genome.fa' \
    --chrom_sizes '/ref/hg38.chrom.sizes' \
    --hotspot_center_sites '/ref/hotspot2/hg38.center_sites.n100.starch' \
    --hotspot_mappable '/ref/hotspot2/hg38.mappable_only.bed' \
    --rgt_data '/ref/rgtdata' \
    --blacklist '/ref/hg38-blacklist.v2.bed' \
    --outdir results/ \
    -resume

Drop `--rgt_data` and add `--skip_footprint` to stop after hotspot calling.

SLURM HPC

The `slurm` profile runs through Singularity, which cannot resolve the default Docker image name, so pass the converted `.sif` with `--container`:

singularity build pipeline-dnaseseq.sif docker-daemon://encode-toolkit/pipeline-dnaseseq:1.0.0

nextflow run scripts/main.nf \
    -profile slurm \
    --container /path/to/pipeline-dnaseseq.sif \
    --reads '/data/fastq/*_R{1,2}.fastq.gz' \
    --bwa_index '/ref/bwa_index/genome.fa' \
    --chrom_sizes '/ref/hg38.chrom.sizes' \
    --hotspot_center_sites '/ref/hotspot2/hg38.center_sites.n100.starch' \
    --hotspot_mappable '/ref/hotspot2/hg38.mappable_only.bed' \
    --rgt_data '/ref/rgtdata' \
    --blacklist '/ref/hg38-blacklist.v2.bed' \
    --outdir results/ \
    -resume

Cloud (GCP / AWS)

# Google Cloud Batch
nextflow run scripts/main.nf -profile gcp \
    --container us-docker.pkg.dev/<project>/<repo>/pipeline-dnaseseq:1.0.0 \
    --gcp_project <project> \
    --gcp_workdir gs://<bucket>/work \
    --reads 'gs://<bucket>/fastq/*_R{1,2}.fastq.gz' \
    --bwa_index gs://<bucket>/ref/bwa_index/genome.fa \
    --chrom_sizes gs://<bucket>/ref/hg38.chrom.sizes \
    --hotspot_center_sites gs://<bucket>/ref/hotspot2/hg38.center_sites.n100.starch \
    --hotspot_mappable gs://<bucket>/ref/hotspot2/hg38.mappable_only.bed \
    --rgt_data gs://<bucket>/ref/rgtdata \
    --blacklist gs://<bucket>/ref/hg38-blacklist.v2.bed \
    --outdir gs://<bucket>/results

# AWS Batch
nextflow run scripts/main.nf -profile aws \
    --container <account>.dkr.ecr.<region>.amazonaws.com/pipeline-dnaseseq:1.0.0 \
    --aws_queue <job-queue> \
    --aws_workdir s3://<bucket>/work \
    --reads 's3://<bucket>/fastq/*_R{1,2}.fastq.gz' \
    --bwa_index s3://<bucket>/ref/bwa_index/genome.fa \
    --chrom_sizes s3://<bucket>/ref/hg38.chrom.sizes \
    --hotspot_center_sites s3://<bucket>/ref/hotspot2/hg38.center_sites.n100.starch \
    --hotspot_mappable s3://<bucket>/ref/hotspot2/hg38.mappable_only.bed \
    --rgt_data s3://<bucket>/ref/rgtd