nf-core/bacass

What nf-core/bacass is

nf-core/bacass is a bioinformatics pipeline designed for the de novo assembly and annotation of bacterial genomes. Initiated by Andreas Wilm, originally written by Alex Peltzer, updated to Nextflow DSL2 by Daniel Straub, and maintained by Daniel Valle-Millares, it provides standard workflows for processing bacterial sequencing data.

Bacterial genome assembly requires different strategies depending on whether data originates from short-read platforms, Oxford Nanopore long reads, or a combination of both. The pipeline addresses this by providing automated paths for read quality control, coverage downsampling, read filtering, assembly, polishing, contamination checking, assembly validation, and downstream structural and functional annotation.

What the pipeline does

Users supply sequencing inputs and metadata through a tab-delimited sample sheet containing single- or paired-end short reads, long reads, optional Fast5 files, and expected genome sizes. For short reads, adapter trimming and quality filtering are executed using FastP, accompanied by quality checks via FastQC. For Nanopore data, reads can be downsampled with Rasusa, trimmed with Porechop, or filtered with Filtlong, with quality visualised using NanoPlot and PycoQC. Read libraries are assessed for purity and contamination using Kraken2 and Kmerfinder.

Assembly is performed according to the chosen input data type: short reads are assembled with Unicycler or MEGAHIT; long reads are assembled using Unicycler, Miniasm with Racon, Canu, Flye, Raven, Autocycler, or Dragonflye; and hybrid datasets are processed using Unicycler or Dragonflye. Long-read assemblies can be polished using Medaka or Nanopolish when Fast5 files are provided. Completed assemblies are assessed for structural metrics using QUAST and gene completeness using BUSCO, followed by bacterial annotation using Prokka, Bakta, or DFAST. When Kmerfinder is enabled, samples are grouped by matching reference genomes for comparative QUAST analysis.

Key facts

What you can use it for

Short-read de novo bacterial assembly

Assemble Illumina bacterial sequencing datasets using Unicycler or MEGAHIT following automated quality trimming with FastP.

Nanopore long-read assembly and polishing

Assemble Oxford Nanopore reads with dedicated long-read assemblers such as Flye, Canu, or Raven, with optional signal-level polishing via Nanopolish or neural-network polishing via Medaka.

Hybrid genome assembly

Combine short reads and long reads using Unicycler or Dragonflye to generate high-continuity bacterial draft assemblies.

Contamination screening and sample purity verification

Screen bacterial isolate reads against reference databases with Kraken2 and Kmerfinder to check taxonomic identity and identify mixed cultures.

Automated bacterial genome annotation

Annotate assembled bacterial contigs using Prokka, Bakta, or DFAST to predict coding sequences and functional genomic features.

Run it here

The research agent runs nf-core/bacass 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

Questions

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.