{"doi":"10.1101/2025.08.04.668502","title":"Defining and cataloging variants in pangenome graphs","abstract":"Abstract Structural variation causes some human haplotypes to align poorly with the linear reference genome, leading to ‘reference bias’. A pangenome reference graph could ameliorate this bias by relating a sample to multiple reference assemblies. However, this approach requires a new definition of a ‘genetic variant.’ We introduce a definition of pangenome variants and a method, pantree , to identify them. Our approach involves a pangenome reference tree which includes all nodes (sequences) of the pangenome graph, but only a subset of its edges; non-reference edges are variant edges . Our variants are biallelic and have well-defined positions. Analyzing the Minigraph-Cactus draft human pangenome reference graph, we identified 29.6 million genetic variants. Most variants (99.2%) are small, and most small variants (73.9%) are SNPs. 3.5 million variants (11.7%) have a reference allele which is not on GRCh38; these variants are difficult to detect without a pangenome reference, or with existing pangenome-based approaches. They tend to be embedded within tangled, multiallelic regions. We analyze two medically relevant regions, around the HLA-A and RHD genes, identifying thousands of small variants embedded within several large insertions, deletions, and inversions. We release an open-source software tool together with a VCF variant catalogue.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":556634,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":2,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9582,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1456321,"name":"Shenghan Zhang","orcid":null,"position":1,"is_corresponding":false},{"id":1455868,"name":"Hongqiao Hu","orcid":"0000-0001-8175-5648","position":2,"is_corresponding":false},{"id":1455869,"name":"Heng Li","orcid":"0000-0002-1484-2845","position":3,"is_corresponding":false},{"id":230095,"name":"Luke J. O’Connor","orcid":"0000-0003-2730-9668","position":4,"is_corresponding":false},{"id":1455867,"name":"Pouria Salehi Nowbandegani","orcid":"0000-0002-3659-0765","position":0,"is_corresponding":true}],"reference_count":14,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:55:08.896385Z","pmid":"40799530","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":[]}