{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:11:01Z","timestamp":1772165461788,"version":"3.50.1"},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T00:00:00Z","timestamp":1621468800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T00:00:00Z","timestamp":1621468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01MH107205"],"award-info":[{"award-number":["R01MH107205"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R24OD024622"],"award-info":[{"award-number":["R24OD024622"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01TR002623"],"award-info":[{"award-number":["U01TR002623"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01HG007530"],"award-info":[{"award-number":["U01HG007530"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006823","name":"Boston Children's Hospital","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006823","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Whole exome sequencing (WES) is widely adopted in clinical and research settings; however, one of the practical concerns is the potential false negatives due to incomplete breadth and depth of coverage for several exons in clinically implicated genes. In some cases, a targeted gene panel testing may be a dependable option to ascertain true negatives for genomic variants in known disease-associated genes. We developed a web-based tool to quickly gauge whether all genes of interest would be reliably covered by WES or whether targeted gene panel testing should be considered instead to minimize false negatives in candidate genes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      <jats:italic>WEScover<\/jats:italic>\n                      is a novel web application that provides an intuitive user interface for discovering breadth and depth of coverage across population-scale WES datasets, searching either by phenotype, by targeted gene panel(s) or by gene(s). Moreover, the application shows metrics from the Genome Aggregation Database to provide gene-centric view on breadth of coverage.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      <jats:italic>WEScover<\/jats:italic>\n                      allows users to efficiently query genes and phenotypes for the coverage of associated exons by WES and recommends use of panel tests for the genes with potential incomplete coverage by WES.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-021-04178-5","type":"journal-article","created":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T16:02:30Z","timestamp":1621526550000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["WEScover: selection between clinical whole exome sequencing and gene panel testing"],"prefix":"10.1186","volume":"22","author":[{"given":"In-Hee","family":"Lee","sequence":"first","affiliation":[]},{"given":"Yufei","family":"Lin","sequence":"additional","affiliation":[]},{"given":"William Jefferson","family":"Alvarez","sequence":"additional","affiliation":[]},{"given":"Carles","family":"Hernandez-Ferrer","sequence":"additional","affiliation":[]},{"given":"Kenneth D.","family":"Mandl","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4877-7567","authenticated-orcid":false,"given":"Sek Won","family":"Kong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,5,20]]},"reference":[{"key":"4178_CR1","unstructured":"Stavropoulos DJ, Merico D, Jobling R, Bowdin S, Monfared N, Thiruvahindrapuram B, Nalpathamkalam T, Pellecchia G, Yuen RKC, Szego MJ et al: Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine. NPJ Genom Med 2016, 1."},{"issue":"5","key":"4178_CR2","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1001\/jamaneurol.2014.405","volume":"71","author":"J Wang","year":"2014","unstructured":"Wang J, Gotway G, Pascual JM, Park JY. Diagnostic yield of clinical next-generation sequencing panels for epilepsy. JAMA Neurol. 2014;71(5):650\u20131.","journal-title":"JAMA Neurol"},{"issue":"2","key":"4178_CR3","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.ajhg.2015.06.009","volume":"97","author":"JX Chong","year":"2015","unstructured":"Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N, Smith JD, Harrell TM, McMillin MJ, Wiszniewski W, Gambin T, et al. The genetic basis of mendelian phenotypes: discoveries, challenges, and opportunities. 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