{"doi":"10.1101/2024.10.27.620212","title":"Integer programming framework for pangenome-based genome inference","abstract":"Abstract Affordable genotyping methods are essential in genomics. Commonly used genotyping methods primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable in highly polymorphic and repetitive regions, further impacting genotyping performance. Recent works highlight the advantage of haplotype-resolved pangenome graphs in addressing these challenges. Building on these developments, we propose a rigorous alignment-free genotyping framework. Our formulation seeks a path through the pangenome graph that maximizes the matches between the path and substrings of sequencing reads (e.g., k -mers) while minimizing recombination events (haplotype switches) along the path. We prove that this problem is NP-Hard and develop efficient integer-programming solutions. We benchmarked the algorithm using downsampled short-read datasets from homozygous human cell lines with coverage ranging from 0.1× to 10×. Our algorithm accurately estimates complete major histocompatibility complex (MHC) haplotype sequences with small edit distances from the ground-truth sequences, providing a significant advantage over existing methods on low-coverage inputs. Although our algorithm is designed for haploid samples, we discuss future extensions to diploid samples. Implementation https://github.com/at-cg/PHI","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2024,"id":492258,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9467,"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":1338077,"name":"Md Helal Hossen","orcid":"0000-0002-9785-3792","position":1,"is_corresponding":false},{"id":988631,"name":"Stephan Scholz","orcid":"0000-0002-8383-9498","position":2,"is_corresponding":false},{"id":19739,"name":"Alexander T Dilthey","orcid":"0000-0002-6394-4581","position":3,"is_corresponding":false},{"id":1338078,"name":"Daniel Gibney","orcid":"0000-0003-1493-5432","position":4,"is_corresponding":false},{"id":241559,"name":"Chirag Jain","orcid":"0000-0002-4300-0794","position":5,"is_corresponding":false},{"id":1338076,"name":"Ghanshyam Chandra","orcid":"0000-0001-7687-4132","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:08:49.768795Z","pmid":"39554168","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":[]}