nf-core pipeline · genome-assembly-evaluation, genomics, phylogenetic-trees
nf-core/genomeqc
A bioinformatics pipeline for evaluating and comparing the quality of multiple genome assemblies and annotations.
What nf-core/genomeqc is
nf-core/genomeqc is a bioinformatics pipeline designed to benchmark and evaluate multiple genome assemblies side by side, alongside their corresponding gene annotations. It was originally created by Chris Wyatt and Fernando Duarte at University College London.
Evaluating newly assembled genomes or choosing among publicly available alternatives often requires running multiple disparate assessment tools for assembly contiguity, completeness, contamination, and structural annotations. nf-core/genomeqc resolves this fragmentation by automating the execution of standard quality-control software across several genomes simultaneously.
The pipeline ingests local assembly files or automated downloads from NCBI, standardises evaluations, and produces comparative reports including an interactive application, tabular files, and visual summaries to guide genomic quality assessment.
What the pipeline does
The workflow begins by accepting user-provided FASTA and GFF files or retrieving assemblies and annotations directly from NCBI using NCBI genome download. For assembly assessment, it computes completeness using BUSCO single-copy markers (and generates BUSCO Ideograms for chromosomes containing markers), calculates contiguity statistics like N50 and GC percentage via QUAST, screens for foreign organism or adaptor contamination using FCS-GX, FCS-adaptor, and Tiara, and optionally identifies telomeric repeats via tidk, sequencing-read-based completeness via Merqury, or transposable elements via HiTE or RepeatMasker (with optional RepeatModeler de novo library construction and MMseqs2 dereplication).
For annotation evaluation, AGAT calculates gene counts and feature lengths, and the pipeline quantifies overlapping genes. Protein sequences from the longest isoforms are extracted using GffRead and passed to OrthoFinder to identify orthologous gene sets. Using either the identified orthology or BUSCO markers if no annotations are provided, it constructs a phylogenetic tree displayed in conventional or circular layout alongside quality metrics. The run concludes by generating MultiQC outputs, custom HTML and Excel reports, and an executable that launches an interactive Shiny application for tree and metric customisation.
Key facts
- Pipeline engine
- Nextflow (nf-core)
- Original developers
- Chris Wyatt and Fernando Duarte (University College London)
- Latest release
- 1.0.0 (2026-09-01)
- Input formats
- CSV samplesheet specifying FASTA, GFF3, or NCBI accessions
- Core metrics evaluated
- Assembly contiguity, completeness, contamination, telomeres, transposable elements, and gene annotation statistics
- Primary outputs
- Phylogenetic tree summaries, custom HTML and Excel reports, MultiQC report, Shiny app executable
- Phylogenetic tree minimum
- At least 3 assemblies required
What you can use it for
- Multi-assembly benchmarking
- Compare assembly contiguity metrics, N50 values, and BUSCO completeness scores across multiple assembly iterations or algorithms for the same organism.
- Cross-species comparative genomics QC
- Assess assembly quality and gene annotation completeness across a clade of related organisms using OrthoFinder and BUSCO marker-based trees.
- Genomic contamination and repeat screening
- Identify vector, adaptor, or foreign-organism contaminations using NCBI FCS tools and Tiara while simultaneously cataloguing transposable element content.
- Annotation quality verification
- Inspect gene feature counts, structural lengths, and overlapping gene instances across annotated genomes using AGAT and GffRead.
Run it here
The research agent runs nf-core/genomeqc 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 local FASTA and GFF inputs as well as automated retrieval using NCBI accessions within a single samplesheet.
- Can run on assemblies lacking annotations by automatically skipping annotation-dependent analyses and basing tree construction on BUSCO markers.
- Generates both conventional and circular phylogenetic trees integrated with quality metrics scored as colour-blind-safe traffic lights.
- Provides an interactive Shiny application executable allowing real-time adjustment and export of tree visualisations.
Watch out for
- Phylogenetic tree summaries require a minimum of three assemblies to be plotted.
- Setting the BUSCO lineage parameter to auto can cause failures during the lineage determination phase.
- Generating de novo repeat libraries using RepeatModeler is computationally slow, taking 24 to 48 hours per genome.
- BUSCO Ideogram plotting only visualises chromosomes or scaffolds containing at least one single-copy marker.
Questions
Can I run nf-core/genomeqc without my own cluster?
The research agent runs nf-core/genomeqc 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/genomeqc under?
MIT, like every nf-core pipeline.
Can nf-core/genomeqc run if I do not have gene annotations for my genomes?
Yes. If no annotation GFF files are supplied, the pipeline will ignore steps involving gene statistics and build the phylogenetic tree using BUSCO markers rather than OrthoFinder orthologues.
How many genome assemblies do I need to supply?
While the pipeline can process individual genomes for general quality metrics, the tree summary plot requires at least three assemblies to be generated.
What is the recommended setting for BUSCO lineage?
It is strongly recommended to explicitly define the lineage using the --busco_lineage parameter, as leaving it on the default auto setting can lead to issues during lineage detection.
Can I mix NCBI accessions with local FASTA and GFF files?
Yes. The pipeline input samplesheet supports combining NCBI accessions and paths to local files across different rows.
What tools handle transposable element (TE) annotation?
TE annotation is optional and can be run using either HiTE for fast alignment-free identification or RepeatMasker with DFAM famdb, alongside optional RepeatModeler de novo library generation.
How to cite it
Written from nf-core/genomeqc's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.