2026-07-24T11:55:07Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:20648 2024-11-27T23:18:02Z ddc:004 open_access

MEM-Based Pangenome Indexing for k-mer Queries Hwang, Stephen Brown, Nathaniel K. Ahmed, Omar Y. Jenike, Katharine M. Kovaka, Sam Schatz, Michael C. Langmead, Ben Pangenomics Comparative genomics Compressed indexing Pangenomes are growing in number and size, thanks to the prevalence of high-quality long-read assemblies. However, current methods for studying sequence composition and conservation within pangenomes have limitations. Methods based on graph pangenomes require a computationally expensive multiple-alignment step, which can leave out some variation. Indexes based on k-mers and de Bruijn graphs are limited to answering questions at a specific substring length k. We present Maximal Exact Match Ordered (MEMO), a pangenome indexing method based on maximal exact matches (MEMs) between sequences. A single MEMO index can handle arbitrary-length queries over pangenomic windows. MEMO enables both queries that test k-mer presence/absence (membership queries) and that count the number of genomes containing k-mers in a window (conservation queries). MEMO’s index for a pangenome of 89 human autosomal haplotypes fits in 2.04 GB, 8.8× smaller than a comparable KMC3 index and 11.4× smaller than a PanKmer index. MEMO indexes can be made smaller by sacrificing some counting resolution, with our decile-resolution HPRC index reaching 0.67 GB. MEMO can conduct a conservation query for 31-mers over the human leukocyte antigen locus in 13.89 seconds, 2.5× faster than other approaches. MEMO’s small index size, lack of k-mer length dependence, and efficient queries make it a flexible tool for studying and visualizing substring conservation in pangenomes. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Stephen Hwang and Nathaniel K. Brown and Omar Y. Ahmed and Katharine M. Jenike and Sam Kovaka and Michael C. Schatz and Ben Langmead 2024 Is Part Of LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.WABI.2024.4 urn:nbn:de:0030-drops-206482 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.4 eng https://creativecommons.org/licenses/by/4.0/legalcode