{"doi":"10.1101/2021.03.23.436571","title":"Comparative genome analysis using sample-specific string detection in accurate long reads","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Motivation</jats:title>\n                  <jats:p>Comparative genome analysis of two or more whole-genome sequenced (WGS) samples is at the core of most applications in genomics. These include discovery of genomic differences segregating in population, case-control analysis in common diseases, and rare disorders. With the current progress of accurate long-read sequencing technologies (e.g., circular consensus sequencing from PacBio sequencers) we can dive into studying repeat regions of genome (e.g., segmental duplications) and hard-to-detect variants (e.g., complex structural variants).</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>\n                    We propose a novel framework for addressing the comparative genome analysis by discovery of strings that are specific to one genome (“samples-specific” strings). We have developed an accurate and efficient novel method for discovery of samples-specific strings between two groups of WGS samples. The proposed approach will give us the ability to perform comparative genome analysis without the need to map the reads and is not hindered by shortcomings of the reference genome. We show that the proposed approach is capable of accurately finding samples-specific strings representing nearly all variation (\n                    <jats:italic>&gt;</jats:italic>\n                    98%) reported across pairs or trios of WGS samples using accurate long reads (e.g., PacBio HiFi data).\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Availability</jats:title>\n                  <jats:p>\n                    The proposed tool is publicly available at\n                    <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" ext-link-type=\"uri\" xlink:href=\"https://github.com/Parsoa/PingPong\">https://github.com/Parsoa/PingPong</jats:ext-link>\n                    .\n                  </jats:p>\n                </jats:sec>","journal":null,"year":null,"id":592171,"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":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1338107,"name":"Luca Denti","orcid":"0000-0001-8786-2276","position":1,"is_corresponding":false},{"id":351124,"name":"Paola Bonizzoni","orcid":"0000-0001-7289-4988","position":3,"is_corresponding":false},{"id":550281,"name":"Rayan Chikhi","orcid":"0000-0003-1099-8735","position":4,"is_corresponding":false},{"id":35201,"name":" Fereydoun Hormozdiari","orcid":"0000-0003-2703-9274","position":5,"is_corresponding":false},{"id":1515267,"name":"Parsoa Khorsand","orcid":"0000-0002-4222-4788","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Comparative genome analysis using sample-specific string detection in accurate long reads","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Motivation</jats:title>\n                  <jats:p>Comparative genome analysis of two or more whole-genome sequenced (WGS) samples is at the core of most applications in genomics. These include discovery of genomic differences segregating in population, case-control analysis in common diseases, and rare disorders. With the current progress of accurate long-read sequencing technologies (e.g., circular consensus sequencing from PacBio sequencers) we can dive into studying repeat regions of genome (e.g., segmental duplications) and hard-to-detect variants (e.g., complex structural variants).</jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>\n                    We propose a novel framework for addressing the comparative genome analysis by discovery of strings that are specific to one genome (“samples-specific” strings). We have developed an accurate and efficient novel method for discovery of samples-specific strings between two groups of WGS samples. The proposed approach will give us the ability to perform comparative genome analysis without the need to map the reads and is not hindered by shortcomings of the reference genome. We show that the proposed approach is capable of accurately finding samples-specific strings representing nearly all variation (\n                    <jats:italic>&gt;</jats:italic>\n                    98%) reported across pairs or trios of WGS samples using accurate long reads (e.g., PacBio HiFi data).\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Availability</jats:title>\n                  <jats:p>\n                    The proposed tool is publicly available at\n                    <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" ext-link-type=\"uri\" xlink:href=\"https://github.com/Parsoa/PingPong\">https://github.com/Parsoa/PingPong</jats:ext-link>\n                    .\n                  </jats:p>\n                </jats:sec>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26657633","pmcid":null,"openalex_id":"https://openalex.org/W3136318994","authors":[],"funders":[{"funder_name":"European Commission","grant_id":"872539","title":"Pan-genome Graph Algorithms and Data Integration"},{"funder_name":"French National Research Agency (ANR)","grant_id":"ANR-16-CONV-0005","title":null},{"funder_name":"French National Research Agency (ANR)","grant_id":"ANR-19-P3IA-0001","title":null},{"funder_name":"National Science Foundation","grant_id":"2042518","title":"CAREER: Computational methods to improve our understanding of the diversity of genomic structural variation"},{"funder_name":"European Commission","grant_id":"956229","title":"ALgorithms for PAngenome Computational Analysis"}],"total_grants":5,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2022,"count":1}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/03/23/2021.03.23.436571.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/03/23/2021.03.23.436571.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2021.03.23.436571","host_type":"publisher"},{"url":"https://doi.org/10.1101/2021.03.23.436571","host_type":"repository"},{"url":"https://doi.org/10.1093/bioadv/vbab005","host_type":""},{"url":"https://academic.oup.com/bioinformaticsadvances/article-pdf/1/1/vbab005/41153301/vbab005.pdf","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/36700094","host_type":""},{"url":"http://dx.doi.org/10.1093/bioadv/vbab005","host_type":""},{"url":"https://dx.doi.org/10.1101/2021.03.23.436571","host_type":""},{"url":"https://dx.doi.org/10.1093/bioadv/vbab005","host_type":""},{"url":"https://hdl.handle.net/10281/337527","host_type":""},{"url":"https://escholarship.org/content/qt23z7x5m6/qt23z7x5m6.pdf","host_type":""},{"url":"https://escholarship.org/uc/item/23z7x5m6","host_type":""},{"url":"https://doi.org/https://doi.org/10.1093/bioadv/vbab005","host_type":""}],"fields_of_study":["Genomics and Phylogenetic Studies","Genetic diversity and population structure","Chromosomal and Genetic Variations","0301 basic medicine","Computer science","0206 medical engineering","String (computer science)","Pattern recognition","02 engineering and technology","Sample (graphics)","Genome","03 medical and health sciences","Artificial intelligence","FM-index"],"mesh_terms":[],"keywords":["Genome","Computational biology","Comparative genomics","Reference genome","Biology","Genomics","Structural variation","String (physics)","Genetics","Computer science","Gene","Mathematics","Human Genome","Bioinformatics and Computational Biology","Bioengineering","General Medicine","Biological Sciences","Original Article","Long reads, FM-index, structural variants;","Human Genome Structural Variant Consortium","Biotechnology"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-26T12:30:09.499301Z","pmid":null,"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":[]}