hgt-site

hgt-site finds places where DNA from bacteria or other organisms may have been inserted into a host genome, such as a human genome, using sequencing data. Most bacterial reads in these samples come from contamination or from DNA fragments joined by chance in the lab, so hgt-site checks each possible site against what chance alone would produce and keeps only the sites with clearly more support.

It takes paired-end reads aligned to the host (BAM, CRAM or SAM) and Kraken2 classifications of the reads that did not align, and writes a table of candidate sites, with optional BED, VCF and MultiQC files. Where reads cross the junction itself, the insertion point is given to the base pair. It works with any host alignment and Kraken2 output, including the files produced by nf-core/hgtseq.

In benchmarks on real human and bacterial genomes with added contamination, hgt-site reported no false sites across 18 runs on fresh random seeds. It is also fast: on a sample of 2.1 million reads it took about 3 seconds once the reads were aligned and classified, against about 2.5 minutes for LGTSeek.

Installation

pip install hgt-site

Usage

hgt-site run \
  --bam sample.bam \
  --kraken-db /path/to/kraken2-db \
  --host-taxid 9606 \
  --threads 8 \
  -o sample.hgt-site.tsv \
  --bed sample.hgt-site.bed \
  --vcf sample.hgt-site.vcf

This classifies the unmapped reads with Kraken2 and calls the sites in one step, and needs kraken2 on PATH. If the reads have already been classified, use hgt-site call --kraken sample.kraken2.txt instead, which accepts several files at once.

To try it on simulated data with known insertion sites:

hgt-site simulate -o demo
hgt-site call --bam demo.sam --kraken demo.kraken2.txt --host-taxid 9606 -o demo.tsv

Documentation and benchmarks

Full documentation: https://iraajgangavaram.github.io/hgt-site/

Source code, benchmark scripts and results: https://github.com/iraajgangavaram/hgt-site

Citation

If you use hgt-site, please cite it: https://doi.org/10.5281/zenodo.23842712

Licence

MIT