nf-core pipeline · ampliconarchitect, ampliconsuite, circle-seq
nf-core/circdna
A Nextflow pipeline identifying extrachromosomal circular DNA from Circle-seq, WGS, and ATAC-seq data.
What nf-core/circdna is
nf-core/circdna is a bioinformatics analysis pipeline designed to identify extrachromosomal circular DNAs (ecDNAs) in cancer and other eukaryotic cells. It processes short-read sequencing data across multiple modalities, including Circle-seq, whole-genome sequencing (WGS), and ATAC-seq, to detect circular DNA species spanning from small eccDNAs or microDNAs to large, amplified circular structures.
Originally authored by Daniel Schreyer at the University of Glasgow's Institute of Cancer Sciences as part of the PRECODE project, the pipeline consolidates several established computational tools into a unified, reproducible Nextflow DSL2 workflow using isolated software containers per process.
The pipeline allows researchers to explore the landscape of circular DNA molecules across various sequencing types, providing multiple specialised analysis branches according to data type and biological objectives.
What the pipeline does
The workflow begins by merging re-sequenced FASTQ files if required, assessing initial sequence quality with FastQC, and performing adapter and quality trimming using Trim Galore!. Short reads are then aligned to a reference genome with BWA-MEM, followed by sorting and indexing with SAMtools. Alternatively, aligned paired-end BAM files can be provided directly as input.
Users then select a dedicated circular DNA detection branch using the circle_identifier setting. Available routes include Circle-Map (utilising Circle-Map ReadExtractor followed by either Circle-Map Realign or Circle-Map Repeats for repetitive elements), CIRCexplorer2, Circle_finder (preceded by Samblaster), AmpliconArchitect through the AmpliconSuite-Pipeline for amplified amplicons, or de novo circular assembly via Unicycler combined with Minimap2 alignment. Quality metrics and summary reports are aggregated at the end using MultiQC.
Key facts
- Supported inputs
- Paired-end FASTQ or BAM files
- Sequencing types
- Circle-seq, WGS, ATAC-seq
- Underlying framework
- Nextflow DSL2 with Docker/Singularity containers
- Identifier algorithms
- Circle-Map, CIRCexplorer2, Circle_finder, AmpliconArchitect, Unicycler
- Latest release
- 1.1.0 (2024-02-10)
What you can use it for
- Junction-based eccDNA identification from Circle-seq or ATAC-seq
- Discover putative circular DNA breakpoint junctions and smaller eccDNA or microDNA structures using tools such as Circle-Map, CIRCexplorer2, or Circle_finder.
- Detection of repetitive circular DNA
- Identify circular DNA derived from repetitive genomic elements using Circle-Map Repeats on ATAC-seq or Circle-seq datasets.
- Amplified ecDNA detection in cancer genomes
- Identify focal circular amplicons and ecDNA architecture from whole-genome sequencing datasets via the AmpliconArchitect workflow.
- De novo circular genome assembly
- Reconstruct full-length extrachromosomal circular sequences directly from Circle-seq data using Unicycler de novo assembly and Minimap2.
Run it here
The research agent runs nf-core/circdna 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
- Consolidates multiple established circular DNA discovery algorithms into a single configurable workflow.
- Supports multiple input data types, including paired-end FASTQ reads and pre-aligned BAM files.
- Implements Nextflow DSL2 with process-level containerisation to ensure computational portability and reproducibility.
- Includes automated continuous integration tests run on full-sized datasets using AWS cloud infrastructure.
Watch out for
- Certain analysis branches and tools are restricted to specific input sequencing types, such as AmpliconArchitect requiring WGS data.
- Running the AmpliconArchitect branch requires external dependencies including a local Mosek licence file and data repository.
- Samblaster combined with Circle_finder cannot be used with filtered BAM files where duplicates are removed.
- Input sequencing data is limited to short-read paired-end formats.
Questions
Can I run nf-core/circdna without my own cluster?
The research agent runs nf-core/circdna 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/circdna under?
MIT, like every nf-core pipeline.
What sequencing technologies and assay types are compatible?
The pipeline processes short-read paired-end sequencing data from Circle-seq, whole-genome sequencing (WGS), and ATAC-seq.
How are different circular DNA discovery tools chosen?
Users select an identification tool using the circle_identifier parameter. Available identifiers include circle_finder, circexplorer2, circle_map_realign, circle_map_repeats, ampliconarchitect, and unicycler.
What is needed to run the AmpliconArchitect branch?
Using the ampliconarchitect route requires supplying paths to an AmpliconSuite data repository (via --aa_data_repo) and a directory containing a mosek.lic licence file (via --mosek_license_dir).
Can pre-aligned BAM files be used instead of raw sequencing reads?
Yes, the pipeline accepts sample sheets listing either paired-end FASTQ files or single BAM files generated from paired-end reads by configuring the input_format option.
How to cite it
10.5281/zenodo.6685250
Written from nf-core/circdna's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.