{"paper_id":"21f3cdbf-579e-4cd5-b722-8de1faf12ffd","body_text":"Bridging Short- and Long-Read Structural Variation Detection with SurVeyor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Bridging Short- and Long-Read Structural Variation Detection with SurVeyor Wing-Kin Sung, Ramesh Rajaby, Tetsuo Shibuya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7732239/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Structural variations (SVs) are a major source of genomic diversity and disease, yet accurate detection and genotyping with short-read sequencing remain a longstanding challenge, with existing approaches missing large fractions of variants. We present SurVeyor, a unified, cohort-aware pipeline that significantly advances the state of the art for SV discovery and genotyping from short reads. Using public data, we found SurVeyor to outperform all tested tools, academic and commercial, both for SV discovery and genotyping. Furthermore, SurVeyor can leverage cohort data to yield even more complete callsets. Applied to a cohort of 63 individuals, SurVeyor achieved more than twice the sensitivity of existing short-read pipelines, and almost matched the sensitivity while exceeding the precision of state-of-the-art PacBio HiFi long-read callers. Overall, SurVeyor bridges the performance gap between short and long-reads SV detection and between academic and commercial pipelines, enabling population-scale and resource-limited studies to generate reliable SV catalogues without dependence on costly technologies. Biological sciences/Computational biology and bioinformatics/Genome informatics Biological sciences/Genetics/Genomics Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7732239\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":523306064,\"identity\":\"d9a98067-8981-4527-a107-c2b5a070dcbe\",\"order_by\":0,\"name\":\"Wing-Kin Sung\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIie3RMQrCMBSA4RShk8X1lWi9QiWjl0kpJEvr7FAlIMTRtYt4BUfHQiEuPYAncFIodBfbKo5p3QTzQ3jL+0IgCJlMPxggu50eQsNBPesDdj9CvieB6E3clIWVc1rxXRrnPlrOA4El1RIMTGGnOMfpZRFSVPBAjFWmJR7mcuBIFR8hIpkl80AAF11kU9WE+y159CAYsww7MqENoZZoCNM/zD1cmbuX2SwtbsSnihMJjGoJFIqUd7mejrYRgTKZT3bAfC15l79Gc33Hr3xa99wzmUymv+wJ/01C9pk6WBsAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"The Chinese University of Hong Kong\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Wing-Kin\",\"middleName\":\"\",\"lastName\":\"Sung\",\"suffix\":\"\"},{\"id\":523306065,\"identity\":\"bd5586a6-1b85-4cac-b038-50a87640f456\",\"order_by\":1,\"name\":\"Ramesh Rajaby\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0001-9980-1913\",\"institution\":\"University of Tokyo\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ramesh\",\"middleName\":\"\",\"lastName\":\"Rajaby\",\"suffix\":\"\"},{\"id\":523306066,\"identity\":\"e062979b-16e4-409c-834d-d0dfb145ea15\",\"order_by\":2,\"name\":\"Tetsuo Shibuya\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tokyo\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tetsuo\",\"middleName\":\"\",\"lastName\":\"Shibuya\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-09-28 06:45:12\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-7732239/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-7732239/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":95528377,\"identity\":\"45b91afd-d244-4e1c-b291-472ef75f6654\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:15:59\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2489271,\"visible\":true,\"origin\":\"\",\"legend\":\"Article File\",\"description\":\"\",\"filename\":\"main.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7732239/v1_covered_b93d1c7d-e544-47ed-a0a2-a93f10fc8c81.pdf\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e Competing Interest.\",\"formattedTitle\":\"Bridging Short- and Long-Read Structural Variation Detection with SurVeyor\",\"fulltext\":[],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":true,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":true,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"nature-portfolio\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Nature Portfolio\",\"twitterHandle\":\"\",\"acdcEnabled\":false,\"dfaEnabled\":false,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7732239/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7732239/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Structural variations (SVs) are a major source of genomic diversity and disease, yet accurate detection and genotyping with short-read sequencing remain a longstanding challenge, with existing approaches missing large fractions of variants. 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