{"doi":"10.1101/2024.05.20.595044","title":"MEM-based pangenome indexing for <i>k</i> -mer queries","abstract":"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). 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, 2.5x 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.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2024,"id":497792,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9507,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1161504,"name":"Nathaniel K. Brown","orcid":"0000-0002-6201-2301","position":1,"is_corresponding":false},{"id":563544,"name":"Omar Ahmed","orcid":"0000-0002-9933-8508","position":2,"is_corresponding":false},{"id":286353,"name":"Katharine M. Jenike","orcid":"0000-0002-7276-8110","position":3,"is_corresponding":false},{"id":551688,"name":"Sam Kovaka","orcid":"0000-0002-4835-8023","position":4,"is_corresponding":false},{"id":24539,"name":"Michael C. Schatz","orcid":"0000-0002-4118-4446","position":5,"is_corresponding":false},{"id":18148,"name":"Ben Langmead","orcid":"0000-0003-2437-1976","position":6,"is_corresponding":false},{"id":53917,"name":"Stephen Hwang","orcid":"0000-0003-0299-569X","position":0,"is_corresponding":true}],"reference_count":25,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:09:34.764412Z","pmid":"38826299","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}