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bioRxiv · 10.1101/2024.05.20.595044

MEM-based pangenome indexing for k-mer queries

Hwang, S.·Brown, N. K.·Ahmed, O. Y.·Jenike, K. M.·Kovaka, S.·Schatz, M. C.·Langmead, B.
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Abstract

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). MEMOs index for a pangenome of 89 human autosomal haplotypes fits in 2.04 GB, 8.8x smaller than a comparable KMC3 index and 11.4x 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, 2.5x faster than other approaches. MEMOs 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.

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Hwang, S., Brown, N. K., Ahmed, O. Y., Jenike, K. M., Kovaka, S., Schatz, M. C., Langmead, B.. 2024-05-22. MEM-based pangenome indexing for k-mer queries. https://doi.org/10.1101/2024.05.20.595044

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