nf-core pipeline · cutandrun, cutandrun-seq, cutandtag
nf-core/cutandrun
Pipeline for processing CUT&RUN, CUT&Tag, and TIPseq data from raw reads to peak calling and quality reports.
What nf-core/cutandrun is
nf-core/cutandrun is a bioinformatics analysis pipeline designed for data produced by CUT&RUN, CUT&Tag, and TIPseq experimental assays. These molecular techniques are used to profile chromatin accessibility, histone modifications, and protein-DNA interactions. The pipeline was originally written by Chris Cheshire and Charlotte West at the Francis Crick Institute.
The software standardises the processing steps required for low-input epigenomic assays, which often require specialised background controls and calibration methods. It incorporates support for paired IgG negative controls, spike-in genome normalisation, and the removal of linear amplification artefacts associated with targeted insertion methods.
What the pipeline does
The workflow ingests paired-end FASTQ files defined in a samplesheet. Raw reads undergo quality control with FastQC and adapter and quality trimming using Trim Galore!. Reads are subsequently aligned to both the primary target genome and a spike-in reference using Bowtie 2. Alignments are sorted, indexed, and filtered with samtools, and duplicate reads are flagged with Picard. For TIPseq libraries, T7 linear amplification duplicates are filtered out.
Downstream processing generates coverage signal tracks in bedGraph and bigWig formats using bedtools and bedGraphToBigWig. Peaks are called using SEACR, MACS2, or both, followed by consensus peak merging via bedtools. Quality metrics are assessed across multiple dimensions: preseq evaluates library complexity, deepTools produces fragment-size distributions and peak heatmaps, and custom Python scripts calculate peak-based metrics. Integrative Genomics Viewer (IGV) session files are constructed for visual inspection, and all quality statistics are compiled into a MultiQC report.
Key facts
- Pipeline engine
- Nextflow DSL2
- Supported assays
- CUT&RUN, CUT&Tag, TIPseq
- Latest release
- 3.2.2 (2024-02-01)
- Short-read aligner
- Bowtie 2
- Peak callers
- SEACR, MACS2
- Input formats
- Paired-end FASTQ, CSV samplesheet
- Output formats
- BAM, bedGraph, bigWig, BED, MultiQC HTML, IGV session XML
What you can use it for
- Protein-DNA binding site discovery
- Mapping genome-wide transcription factor occupancy or chromatin-associated protein binding using CUT&RUN or CUT&Tag data.
- Spike-in normalised epigenomic profiling
- Aligning reads concurrently to experimental and spike-in genomes to calibrate chromatin modification levels across diverse conditions.
- TIPseq chromatin analysis
- Processing targeted promoter insertion sequencing data with automated elimination of linear T7 amplification duplicates.
Run it here
The research agent runs nf-core/cutandrun with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Integrates both SEACR and MACS2 peak callers with automatic consensus peak set merging.
- Provides built-in handling for dual-genome alignments for spike-in calibration alongside target genome mapping.
- Features dedicated handling for T7 linear amplification duplicate removal in TIPseq protocols.
- Assembles comprehensive quality control metrics across library complexity, fragment lengths, and genomic visualisations into a single MultiQC report.
Watch out for
- Requires paired-end sequencing reads as input via the structured samplesheet.
- Configuration parameters must be provided strictly via command line options or parameter files rather than custom Nextflow configuration files.
Questions
Can I run nf-core/cutandrun without my own cluster?
The research agent runs nf-core/cutandrun with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/cutandrun under?
MIT, like every nf-core pipeline.
Which peak callers are implemented in this pipeline?
The pipeline includes both SEACR and MACS2, which can be selected independently or executed simultaneously to merge consensus peaks.
How are spike-in controls handled?
Bowtie 2 maps sequencing reads against both the primary reference genome and an assigned spike-in genome to facilitate downstream normalisation.
Can the pipeline process single-cell TIPseq datasets?
Yes, it contains explicit support for TIPseq protocols, including the identification and removal of duplicate reads resulting from linear T7 amplification.
What inputs are necessary to begin a run?
Users must supply a CSV samplesheet defining paired-end FASTQ file paths, group names, biological replicates, and corresponding IgG control relationships, along with reference genome identifiers.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/cutandrun's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.