Fast and robust metagenomic sequence comparison through sparse chaining with skani

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani (https://github.com/bluenote-1577/skani), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20x faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets.

Automated summary

This article introduces skani, a sequence comparison tool for metagenome-assembled genomes (MAGs) that overcomes the challenges of high-volume or low-quality data. skani outperforms FastANI in terms of accuracy and speed, being more than 20 times faster for fragmented and incomplete MAGs. It can query genomes against over 65,000 prokaryotic genomes in a matter of seconds and with only 6 GB of memory. skani unlocks higher-resolution insights for extensive and noisy metagenomic datasets.