We ran Mumemto on 474 human assemblies from @humanpangenome.bsky.social to find syntenic regions using MUMs. Mumemto scales remarkably well to large pangenomes thanks to compressed-space algos! It took under 2 days across 7 nodes (each using ~500 GB memory).

Excited to share a preprint for (w/ @benlangmead.bsky.social) our new tool, Mumemto, on biorxiv! Mumemto finds multi-MUMs across pangenomes (i.e. mummer but for pangenomes). It can rapidly visualize synteny, identify misassemblies, and accelerate core genome and multiple alignment, highlighting SVs.

Very excited to see Movi (by @mohsenzakeri.bsky.social) now out in iScience: www.cell.com/iscience/ful.... Movi builds on the "move structure" pangenome index, a compressed full-text index and close cousin to r-index. Compared to r-index, the move structure is simpler and more cache-efficient.

1/5 We (Nate Brown, @oahmed.bsky.social, Travis Gagie, and @benlangmead.bsky.social) developed Movi, a cache-efficient full-text pangenome index.  It's the fastest full-text index for pangenomes, particularly appropriate for adaptive sampling where time budget is important.