{"doi":"10.1093/bioinformatics/btad220","title":"Deep statistical modelling of nanopore sequencing translocation times reveals latent non-B DNA structures","abstract":"MOTIVATION: Non-canonical (or non-B) DNA are genomic regions whose three-dimensional conformation deviates from the canonical double helix. Non-B DNA play an important role in basic cellular processes and are associated with genomic instability, gene regulation, and oncogenesis. Experimental methods are low-throughput and can detect only a limited set of non-B DNA structures, while computational methods rely on non-B DNA base motifs, which are necessary but not sufficient indicators of non-B structures. Oxford Nanopore sequencing is an efficient and low-cost platform, but it is currently unknown whether nanopore reads can be used for identifying non-B structures. RESULTS: We build the first computational pipeline to predict non-B DNA structures from nanopore sequencing. We formalize non-B detection as a novelty detection problem and develop the GoFAE-DND, an autoencoder that uses goodness-of-fit (GoF) tests as a regularizer. A discriminative loss encourages non-B DNA to be poorly reconstructed and optimizing Gaussian GoF tests allows for the computation of P-values that indicate non-B structures. Based on whole genome nanopore sequencing of NA12878, we show that there exist significant differences between the timing of DNA translocation for non-B DNA bases compared with B-DNA. We demonstrate the efficacy of our approach through comparisons with novelty detection methods using experimental data and data synthesized from a new translocation time simulator. Experimental validations suggest that reliable detection of non-B DNA from nanopore sequencing is achievable. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/bayesomicslab/ONT-nonb-GoFAE-DND.","journal":"Bioinformatics","year":2023,"id":364146,"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":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9466,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1118890,"name":"Aaron Zeff Palmer","orcid":"0000-0002-2731-6895","position":1,"is_corresponding":false},{"id":1119393,"name":"William Manka","orcid":null,"position":2,"is_corresponding":false},{"id":49051,"name":"Patrick G. S. Grady","orcid":"0000-0003-0180-7810","position":3,"is_corresponding":false},{"id":1118891,"name":"Venkata S. P. Patchigolla","orcid":"0000-0001-6441-9976","position":4,"is_corresponding":false},{"id":517294,"name":"Jinbo Bi","orcid":"0000-0001-6996-4092","position":5,"is_corresponding":false},{"id":49048,"name":"Rachel J. O’Neill","orcid":"0000-0002-1525-6821","position":6,"is_corresponding":false},{"id":526318,"name":"Zhiyi Chi","orcid":null,"position":7,"is_corresponding":false},{"id":814326,"name":"Derek Aguiar","orcid":"0000-0001-9166-8783","position":8,"is_corresponding":false},{"id":1118889,"name":"Marjan Hosseini","orcid":"0000-0002-0927-6658","position":0,"is_corresponding":true}],"reference_count":71,"raw_metadata":null,"created_at":"2026-07-19T01:14:36.728255Z","pmid":"37387144","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":[]}