nf-core pipeline · bwa-mem, bwa-mem2, fastqc
nf-core/hgtseq
A Nextflow pipeline to identify horizontal gene transfer and host integration sites from sequencing data.
What nf-core/hgtseq is
nf-core/hgtseq is a bioinformatics analysis pipeline designed to investigate horizontal gene transfer events using next-generation sequencing (NGS) data. The workflow was originally developed by Simone Carpanzano and Francesco Lescai within the nf-core community.
Horizontal gene transfer describes the movement of genetic material between distinct organisms outside of parent-to-offspring descent. The pipeline addresses this by applying metagenomic classification to paired-read alignments against a host reference genome, identifying non-host microbial sequences and inferring candidate insertion sites in the host.
What the pipeline does
The pipeline starts by performing quality control on raw reads using FastQC, followed by quality and adapter trimming with Trim Galore, and compilation of quality metrics with MultiQC. Processed reads are then aligned to a host reference genome using BWA.
Using SAMtools, alignment files are sorted, indexed, and filtered by SAM flags to extract paired reads containing unmapped or non-host segments, which are converted back into FASTQ format. These reads are assigned taxonomies using Kraken2 against a designated database. Taxonomic results are plotted using Krona, and an HTML analysis report is generated via R Markdown.
Key facts
- Workflow framework
- Nextflow (DSL2)
- Original authors
- Simone Carpanzano, Francesco Lescai
- Latest release
- 1.1.0
- Input format
- Sample sheet (.csv) and paired-end NGS reads
- Read alignment tool
- BWA / bwa-mem / bwa-mem2
- Alignment processing
- SAMtools
- Taxonomic classification
- Kraken2
- Visualisation and reporting
- FastQC, MultiQC, Krona, R Markdown
What you can use it for
- Identification of microbial integration sites
- Locating genomic positions where non-host microbial sequences integrate into a host genome using discordant paired reads.
- Metagenomic classification of non-host sequences
- Determining the taxonomy of unmapped or partially mapped read pairs from host sequencing datasets using Kraken2.
- Sequencing quality and alignment inspection
- Assessing sequencing quality, adapter contamination, and alignment statistics via automated MultiQC and FastQC reporting.
Run it here
The research agent runs nf-core/hgtseq 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
- Applies Nextflow DSL2 with dedicated software containers per process to ensure reproducibility across compute platforms.
- Runs automated continuous integration testing on full-sized datasets in cloud infrastructure to validate parameters across releases.
- Combines read alignment, flag-based extraction, taxonomic classification, and Krona visualisations into an automated workflow.
Watch out for
- Requires pre-indexed external databases for both Kraken2 and Krona taxonomy.
- Demands user specification of target taxonomy identifiers and reference genomes during execution.
Questions
Can I run nf-core/hgtseq without my own cluster?
The research agent runs nf-core/hgtseq 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/hgtseq under?
MIT, like every nf-core pipeline.
What inputs does nf-core/hgtseq require?
It requires a CSV sample sheet pointing to sequencing reads, a host reference genome, a taxonomy identifier, a Kraken2 database, and a Krona taxonomy file.
How does the pipeline detect horizontal gene transfer events?
It aligns paired reads to a reference genome, extracts reads with SAMtools according to specific SAM flags, and classifies non-host segments taxonomically using Kraken2 to pinpoint potential integration sites.
What tools generate the final visual reports?
Krona provides interactive charts for taxonomic distributions, MultiQC collates read quality reports, and R Markdown compiles the final summary HTML report.
How to cite it
10.5281/zenodo.7244734
Written from nf-core/hgtseq's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.