{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T20:59:50Z","timestamp":1761253190666,"version":"3.37.3"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"22","license":[{"start":{"date-parts":[[2017,8,2]],"date-time":"2017-08-02T00:00:00Z","timestamp":1501632000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["139277"],"award-info":[{"award-number":["139277"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"NSERC","doi-asserted-by":"publisher","award":["249834"],"award-info":[{"award-number":["249834"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Third-generation sequencing (TGS) platforms that generate long reads, such as PacBio and Oxford Nanopore technologies, have had a dramatic impact on genomics research. However, despite recent improvements, TGS reads suffer from high-error rates and the development of read correction methods is an active field of research. This motivates the need to develop tools that can evaluate the accuracy of noisy long reads correction tools.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce LRCstats, a tool that measures the accuracy of long reads correction tools. LRCstats takes advantage of long reads simulators that provide each simulated read with an alignment to the reference genome segment they originate from, and does not rely on a step of mapping corrected reads onto the reference genome. This allows for the measurement of the accuracy of the correction while being consistent with the actual errors introduced in the simulation process used to generate noisy reads. We illustrate the usefulness of LRCstats by analyzing the accuracy of four hybrid correction methods for PacBio long reads over three datasets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>https:\/\/github.com\/cchauve\/lrcstats<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx489","type":"journal-article","created":{"date-parts":[[2017,8,1]],"date-time":"2017-08-01T11:19:46Z","timestamp":1501586386000},"page":"3652-3654","source":"Crossref","is-referenced-by-count":9,"title":["LRCstats, a tool for evaluating long reads correction methods"],"prefix":"10.1093","volume":"33","author":[{"given":"Sean","family":"La","sequence":"first","affiliation":[{"name":"Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada"}]},{"given":"Ehsan","family":"Haghshenas","sequence":"additional","affiliation":[{"name":"School of Computing Science, MADD-Gen program, Simon Fraser University, Burnaby, BC, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9837-1878","authenticated-orcid":false,"given":"Cedric","family":"Chauve","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada"}]}],"member":"286","published-online":{"date-parts":[[2017,8,2]]},"reference":[{"key":"2023051308375198600_btx489-B1","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1038\/nbt.3238","article-title":"Assembling large genomes with single-molecule sequencing and locality-sensitive hashing","volume":"33","author":"Berlin","year":"2015","journal-title":"Nat. Biotechnol"},{"key":"2023051308375198600_btx489-B2","doi-asserted-by":"crossref","first-page":"238.","DOI":"10.1186\/1471-2105-13-238","article-title":"Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): theory and application","volume":"13","author":"Chaisson","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2023051308375198600_btx489-B3","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1038\/nrg.2016.57","article-title":"A comparison of tools for the simulation of genomic next-generation sequencing data","volume":"17","author":"Escalona","year":"2016","journal-title":"Nat. Rev. Genet"},{"key":"2023051308375198600_btx489-B4","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/nrg.2016.49","article-title":"Coming of age: ten years of next-generation sequencing technologies","volume":"17","author":"Goodwin","year":"2016","journal-title":"Nat. Rev. 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Biol"},{"key":"2023051308375198600_btx489-B13","doi-asserted-by":"crossref","first-page":"3506","DOI":"10.1093\/bioinformatics\/btu538","article-title":"LoRDEC: accurate and efficient long read error correction","volume":"30","author":"Salmela","year":"2014","journal-title":"Bioinformatics"},{"key":"2023051308375198600_btx489-B14","doi-asserted-by":"crossref","first-page":"2704","DOI":"10.1093\/bioinformatics\/btw286","article-title":"Simlord: simulation of long read data","volume":"32","author":"St\u00f6cker","year":"2016","journal-title":"Bioinformatics"},{"key":"2023051308375198600_btx489-B15","doi-asserted-by":"crossref","first-page":"56.","DOI":"10.1093\/bib\/bbs015","article-title":"A survey of error-correction methods for next-generation sequencing","volume":"14","author":"Yang","year":"2013","journal-title":"Brief. 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