nf-core pipeline · amplicon, artic, assembly
nf-core/viralrecon
Assembly and intra-host variant calling for viral sequencing data from Illumina and Oxford Nanopore platforms.
What nf-core/viralrecon is
nf-core/viralrecon is a bioinformatics analysis pipeline designed for viral genomics. It performs de novo genome assembly, consensus sequence generation, and intra-host or low-frequency variant calling. The pipeline handles data from both Illumina short-read and Oxford Nanopore long-read platforms.
Originally developed by researchers at the Institute of Health Carlos III (BU-ISCIII) and maintained with the nf-core community primarily by Seqera Labs, the pipeline was built to standardise viral surveillance workflows. It processes shotgun metagenomics sequencing directly from clinical samples as well as target-enrichment protocols, including amplicon-based methods such as the ARTIC SARS-CoV-2 protocol and probe-capture approaches.
The workflow is implemented in Nextflow DSL2 using containerised processes (Docker and Singularity), facilitating reproducible analyses across varied compute infrastructures from local environments to cloud systems.
What the pipeline does
For Illumina data, the pipeline begins by merging technical replicate FASTQ files, running read quality control with FastQC, and trimming adapters using fastp. Host-derived reads can optionally be filtered out using Kraken 2. Alignments are generated using Bowtie 2, followed by SAMtools sorting, duplicate marking via Picard (optional), and amplicon primer removal using iVar where applicable. Variants are identified using iVar (amplicon default) or BCFTools (metagenomics default) and annotated with SnpEff and SnpSift. Consensus sequences are derived using BCFTools or iVar consensus, evaluated with QUAST, and characterised with Pangolin, Nextclade, and Freyja. De novo assembly is performed using SPAdes, Unicycler, or minia after primer trimming with Cutadapt, followed by BLAST alignment to reference, contiguation with ABACAS, and assembly quality assessment via PlasmidID and QUAST.
For Oxford Nanopore data, the workflow aggregates pre-demultiplexed reads using artic guppyplex and runs QC checks with pycoQC and NanoPlot. After optional host read removal with Kraken 2, alignment, variant calling, and consensus generation proceed via the artic minion workflow. Alignment coverage metrics are generated using SAMtools and mosdepth. Downstream analyses include variant annotation via SnpEff and SnpSift, assembly metrics via QUAST, lineage and clade classification using Pangolin and Nextclade, and relative lineage deconvolution using Freyja. Aggregated quality metrics for both platforms are compiled into interactive MultiQC reports.
Key facts
- Pipeline engine
- Nextflow DSL2
- Supported platforms
- Illumina, Oxford Nanopore Technologies
- Primary input formats
- FASTQ, CSV samplesheet, Nanopore sequencing summary
- Supported Illumina protocols
- Metagenomic shotgun, amplicon-based enrichment, probe-capture
- Supported Nanopore protocols
- ARTIC amplicon sequencing
- Short-read aligner
- Bowtie 2
- Variant callers
- iVar, BCFTools, artic minion
- De novo assemblers
- SPAdes, Unicycler, minia
- Lineage and clade tools
- Pangolin, Nextclade, Freyja
- Reporting
- MultiQC, QUAST
What you can use it for
- SARS-CoV-2 Amplicon Surveillance
- Processing Illumina or Nanopore reads generated with ARTIC primer sets to generate consensus genomes, call intra-host variants, and identify lineages via Pangolin and Nextclade.
- Metagenomic Viral Variant Calling
- Filtering host background reads with Kraken 2 and identifying low-frequency variants in clinical shotgun metagenomic datasets using Bowtie 2 and BCFTools.
- De Novo Viral Genome Assembly
- Assembling viral genomes directly from trimmed Illumina reads using assemblers such as SPAdes, Unicycler, or minia, followed by ABACAS contiguation and QUAST assessment.
- Wastewater and Mixed Lineage Deconvolution
- Estimating the relative abundances of distinct viral lineages in mixed samples using Freyja alongside annotated variant calling tables.
Run it here
The research agent runs nf-core/viralrecon 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
- Supports both Illumina short-read and Oxford Nanopore long-read platforms within a single pipeline framework.
- Integrates specialised downstream lineage assignment and deconvolution tools including Pangolin, Nextclade, and Freyja.
- Enables flexible analysis by allowing users to toggle specific components, such as host removal via Kraken 2 or de novo assembly.
- Uses individual containerised processes per task via Nextflow DSL2, ensuring reproducibility and straightforward dependency maintenance.
Watch out for
- Nanopore processing is restricted to amplicon-based sequencing using ARTIC Network primer sets and does not support metagenomic shotgun data.
- Direct SRA downloading within the pipeline is unsupported in versions 2.1 and later, requiring external tools such as nf-core/fetchngs to prepare input data.
- Lineage and clade analysis modules depend on external definitions that require frequent container or database updates as viral variants emerge.
Questions
Can I run nf-core/viralrecon without my own cluster?
The research agent runs nf-core/viralrecon 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/viralrecon under?
MIT, like every nf-core pipeline.
Can nf-core/viralrecon process Nanopore shotgun metagenomics data?
No. Nanopore data processing is exclusively supported for amplicon-based sequencing using ARTIC Network primer schemes.
Which short-read de novo assemblers are available?
The pipeline supports SPAdes, Unicycler, and minia for assembling Illumina reads, followed by contiguation with ABACAS and evaluation with QUAST and PlasmidID.
How are host sequence reads handled?
Host reads can be assessed and filtered out prior to downstream alignment and assembly using Kraken 2, though this step can be bypassed using the --skip_kraken2 option.
How are public datasets from the SRA ingested?
SRA downloading was removed in pipeline version 2.1. Public samples must be downloaded and formatted using an external workflow, such as nf-core/fetchngs, which can generate an input samplesheet directly compatible with viralrecon.
How to cite it
10.5281/zenodo.3901628
Written from nf-core/viralrecon's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.