Vikram Shivakumar

Not saying I agree either way, but one pro for text-based file formats are less dependencies needed for viewing files

This is so amazing, thank you!

comic doodle of Vikram Shivakumar in a sweater and checkered shirt on a pink gradient background, with various elements of the talk to the left: two old moms pointing at MUMs, below an explanation of what those are (large chunks of the same DNA sequence through the genome), at the bottom a few of the organisms worked on: a tomato, a potato, an arabidopsis weed.

#SciArt doodle of @vikramshivakumar.bsky.social's talk yesterday at the @sangerinstitute.bsky.social on MUMs*

*maximal unique matches in pangenomes, now if you did that on sequenced moms you could do mummoms

Excited to share our new preprint on detecting foldback artifacts in long reads with my advisors Matthew Meyerson and @lh3lh3.bsky.social ! Stop by poster C-180 on Wednesday at ISMB/ECCB2025 to learn more and chat!

And of course, the poster itself:

If you’re in Liverpool, stop by my poster A217 at ISMB/EECB 2025, and chat about all things pangenomes, MUMs, and alignment (and the Beatles or Oasis-mania)

Really excited to see this published! To more mum-finding 🍻

🖥️🧬We're thrilled to announce that one of our keynote speakers at #WABI2025 will be the inimitable @benlangmead.bsky.social! wabiconf.github.io/2025/talks/t... Ben's keynote is titled "We are what we index; a primer for the Wheeler Graph era", & it's sure to be a whirlwind tour of full-text indexing!

1/5 We introduce Movi Color, led by Steven Tan (a brilliant undergrad member of Langmead lab) for taxonomic and multi-class classification. It uses a full-text index based on the move structure and does not rely on predefined values (like k-mer length) for index building.
github.com/mohsenzakeri...

GitHub - vikshiv/mumemto: Mumemto: multi-MUM and MEM finding across pangenomes Mumemto: multi-MUM and MEM finding across pangenomes - vikshiv/mumemto

We've released a new version (v1.3) of Mumemto (github.com/vikshiv/mume...) that implements merging. Running Mumemto in merge-mode makes the output set of multi-MUMs dynamic, so adding new assemblies is as easy as computing a new set of MUMs and merging them in.

We can also merge along the shape of a phylogenetic tree, finding clade-specific variation and conserved elements. Previously, adding new assemblies can lose MUMs, which must be present across the whole collection. Now we can find MUMs that reveal local variation distinct to specific subgroups. 3/n

We implement two partition/merge algorithms that can merge multi-MUMs between datasets. This makes Mumemto highly parallelizable, but also very memory efficient if partitions are computed in serial. 2/n

Partitioned Multi-MUM finding for scalable pangenomics Pangenome collections are growing to hundreds of high-quality genomes. This necessitates scalable methods for constructing pangenome alignments that can incorporate newly-sequenced assemblies. We prev...

Excited to share a new update to Mumemto, scaling MUM and conserved element finding to any size pangenome! Preprint out now w/ @benlangmead.bsky.social.
Mumemto scales to the new HPRC v2 release and beyond, and can merge in future assemblies without any recomputation! 1/n

Our pre-print on investigating variation in South Asian genomes is now out!

Thank you to @mikeschatz.bsky.social, @rajivmccoy.bsky.social and @aabiddanda.bsky.social for all their work on this.

🧵 A thread on the key results and takeaways from our work:

If you are here at #bog25 please check out my poster (number 87) tonight! 😁 Showing our work on common variation associated with aneuploidy in human embryos

Excited to share our latest work on comparing and visualizing multiple genome assemblies to identify conservation and structural variation in pangenomes with Mumemto! Check out poster 250 at #bog25 if you are here. New preprint coming very soon 👀

Next up is Nathaniel Brown from @benlangmead.bsky.social's group presenting col-bwt, a new algorithm for computing chain statistics using multi-maximal unique matches.

www.biorxiv.org/content/10.1...

Uncalled4: a toolkit for nanopore signal alignment, analysis and visualization of DNA and RNA modifications.

www.nature.com/articles/s41...

Happy to share our work characterizing functional rare SVs in rare diseases with long-read genome sequencing and transcriptomic outlier data: genome.cshlp.org/content/earl...

Group at the rally by the Lincoln Memorial

Group at the rally by the Lincoln Memorial, with Bill Nye

View along the Reflecting Pool from Lincoln Memorial

Lincoln Memorial

Scenes from #StandUpForScience2025 in DC today. Huge contingent from Johns Hopkins, and also from UMD & DC/Virginia Unis.

GitHub - vikshiv/mumemto: Mumemto: multi-MUM and MEM finding across pangenomes Mumemto: multi-MUM and MEM finding across pangenomes - vikshiv/mumemto

This is possible because we can now merge new assemblies as they are released easily without re-running Mumemto on the whole pangenome! We're just providing the non-zoomable image while we await the final HPRC publication. Preprint: www.biorxiv.org/content/10.1...
Github: github.com/vikshiv/mume...

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).

p.p.s here's a logo I designed for Mumemto (pronounced like memento) inspired by the film.

p.s. Mumemto is already being used to improve read classification with the r-index (www.biorxiv.org/content/10.1...), some great work by Nate Brown.

GitHub - vikshiv/mumemto: Mumemto: multi-MUM and MEM finding across pangenomes Mumemto: multi-MUM and MEM finding across pangenomes - vikshiv/mumemto

We think Mumemto is an essential first-step for pangenome QC and visualization when sequencing new pangenome assembly collections (especially complete and T2T!). Software is here: github.com/vikshiv/mume...

Mumemto can visualize multi-MUM synteny to reveal large-scale pangenome structure. We also showed that multi-MUMs can reveal potential misassemblies (e.g one reported in HPRC v1) and scaffolding errors (contigs are oriented to match a reference w/o the pangenome context revealing a common inversion)

Mumemto uses prefix-free parsing, a compressed-space method to compute the enhance suffix array, to efficiently index large pangenome collections. This makes it quick and memory efficient, with remarkable scaling, enabling multi-MUM computation across hundreds of HPRC assemblies.

Mumemto: efficient maximal matching across pangenomes Aligning genomes into common coordinates is central to pangenome analysis and construction, but it is also computationally expensive. Multi-sequence maximal unique matches (multi-MUMs) are guideposts ...

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.

Mumemto: efficient maximal matching across pangenomes https://www.biorxiv.org/content/10.1101/2025.01.05.631388v1