Fast and robust metagenomic sequence comparison through sparse chaining with skani

Sequence comparison algorithms for metagenome-assembled genomes (MAGs) often have difficulties dealing with data that is high-volume or low-quality. We present skani ( https://github.com/bluenote-1577/skani ), a method for calculating average nucleotide identity (ANI) using sparse approximate alignments. skani is more accurate than FastANI for comparing incomplete, fragmented MAGs while also being > 20 times faster. For searching a database of > 65, 000 prokaryotic genomes, skani takes only seconds per query and 6 GB of memory. skani is a versatile tool that unlocks higher-resolution insights for larger, noisier metagenomic data sets.