ChIP-Seq-Analysis

Generic ChIP-seq Nextflow workflow

Generic ChIP-seq Nextflow workflow

For ChIP-seq, a separate generic Nextflow workflow is available in chipseq_main.nf with configuration in chipseq_nextflow.config.

Why this is generic

• Input FASTQ files are fully controlled by config/chipseq_samples.tsv (no fixed filename pattern is required).
• Sample names can be any value in the sample column.
• The control_sample column pairs each ChIP sample with the exact Input sample ID for downstream bamCompare output.
• Paths and run parameters are set in chipseq_nextflow.config, including reference genome, mapping filters, bigWig options, and bamCompare settings (ratio mode with duplicate ignoring, no scale-factor normalization).

Files

• chipseq_main.nf - ChIP-seq QC, trimming, mapping/filtering, optional bigWig generation, optional ChIP/Input bamCompare, and MultiQC.
• chipseq_nextflow.config - ChIP-seq pipeline parameters and runtime profiles.
• config/chipseq_samples.tsv - sample sheet template; edit file paths, sample IDs, and control_sample pairing.

Quick start

nextflow run chipseq_main.nf -c chipseq_nextflow.config -profile conda -resume

For SLURM:

nextflow run chipseq_main.nf -c chipseq_nextflow.config -profile slurm -resume

Dashboard (for non-terminal users)

A Streamlit dashboard is available at dashboard/app.py to help users who are not comfortable with HPC terminals.

What it supports

• Edit sample metadata and file paths directly in a table (sample name, FASTQ pairs, control pairing).
• Enter HPC login target (username, host, remote working directory) so users can run the pipeline with generated SSH command syntax.
• Set core run parameters (reference paths, MAPQ/filter settings, output directory, profile).
• Save config/chipseq_samples.tsv from the UI.
• Generate a dashboard override config at config/chipseq_dashboard_override.config.
• Launch the Nextflow command from the dashboard (optional).
• Optionally run through SSH (user@host) so execution happens on HPC rather than local machine.
• View a separate QC & Processed Files tab with counts/status for FastQC, fastp, BAM, bigWig, bamCompare outputs, and MultiQC presence.

Run the dashboard

pip install streamlit pandas
streamlit run dashboard/app.py

The dashboard is designed so that users review QC and file status there, and download .bw files later using their normal HPC connection method (SCP/SFTP/Globus).