{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T10:10:55Z","timestamp":1773655855341,"version":"3.50.1"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2018,4,14]],"date-time":"2018-04-14T00:00:00Z","timestamp":1523664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100002803","name":"Fondazione Cariplo","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002803","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic architecture of human diseases. However, a significant proportion of identified genetic variants are actually false positive calls, and this pose serious challenge for variants interpretation. Here, we propose a new tool named Genomic vARiants FIltering by dEep Learning moDels in NGS (GARFIELD-NGS), which rely on deep learning models to dissect false and true variants in exome sequencing experiments performed with Illumina or ION platforms. GARFIELD-NGS showed strong performances for both SNP and INDEL variants (AUC 0.71\u20130.98) and outperformed established hard filters. The method is robust also at low coverage down to 30X and can be applied on data generated with the recent Illumina two-colour chemistry. GARFIELD-NGS processes standard VCF file and produces a regular VCF output. Thus, it can be easily integrated in existing analysis pipeline, allowing application of different thresholds based on desired level of sensitivity and specificity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>GARFIELD-NGS available at https:\/\/github.com\/gedoardo83\/GARFIELD-NGS.<\/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\/bty303","type":"journal-article","created":{"date-parts":[[2018,4,12]],"date-time":"2018-04-12T15:32:51Z","timestamp":1523547171000},"page":"3038-3040","source":"Crossref","is-referenced-by-count":28,"title":["GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS"],"prefix":"10.1093","volume":"34","author":[{"given":"Viola","family":"Ravasio","sequence":"first","affiliation":[{"name":"Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy"}]},{"given":"Marco","family":"Ritelli","sequence":"additional","affiliation":[{"name":"Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy"}]},{"given":"Andrea","family":"Legati","sequence":"additional","affiliation":[{"name":"Unit of Molecular Neurogenetics, Fondazione IRCCS Istituto Neurologico \u2018Carlo Besta\u2019, Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5692-366X","authenticated-orcid":false,"given":"Edoardo","family":"Giacopuzzi","sequence":"additional","affiliation":[{"name":"Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy"}]}],"member":"286","published-online":{"date-parts":[[2018,4,14]]},"reference":[{"key":"2023061313381116600_bty303-B1","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1007\/s00439-016-1656-8","article-title":"Amplicon-based semiconductor sequencing of human exomes: performance evaluation and optimization strategies","volume":"135","author":"Damiati","year":"2016","journal-title":"Hum. 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Protoc. Bioinform"},{"key":"2023061313381116600_bty303-B9","doi-asserted-by":"crossref","first-page":"160.","DOI":"10.3389\/fgene.2013.00160","article-title":"The role and challenges of exome sequencing in studies of human diseases","volume":"4","author":"Wang","year":"2013","journal-title":"Front. Genet"},{"key":"2023061313381116600_bty303-B10","doi-asserted-by":"crossref","first-page":"581.","DOI":"10.1186\/s12864-015-1796-6","article-title":"Comparison and evaluation of two exome capture kits and sequencing platforms for variant calling","volume":"16","author":"Zhang","year":"2015","journal-title":"BMC Genomics"},{"key":"2023061313381116600_bty303-B11","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1038\/nbt.2835","article-title":"Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls","volume":"32","author":"Zook","year":"2014","journal-title":"Nat. Biotechnol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/34\/17\/3038\/50581949\/bioinformatics_34_17_3038.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/34\/17\/3038\/50581949\/bioinformatics_34_17_3038.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T09:39:27Z","timestamp":1686649167000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/34\/17\/3038\/4970515"}},"subtitle":[],"editor":[{"given":"Bonnie","family":"Berger","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2018,4,14]]},"references-count":11,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2018,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bty303","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/149146","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2018,9,1]]},"published":{"date-parts":[[2018,4,14]]}}}