{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T03:23:14Z","timestamp":1775791394944,"version":"3.50.1"},"reference-count":16,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2019,1,12]],"date-time":"2019-01-12T00:00:00Z","timestamp":1547251200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Open Fund Individual Research"},{"DOI":"10.13039\/501100001349","name":"Singapore National Medical Research Council","doi-asserted-by":"crossref","award":["OFIRG15nov072"],"award-info":[{"award-number":["OFIRG15nov072"]}],"id":[{"id":"10.13039\/501100001349","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Somatic Mutation calling method using a Random Forest (SMuRF) integrates predictions and auxiliary features from multiple somatic mutation callers using a supervised machine learning approach. SMuRF is trained on community-curated matched tumor and normal whole genome sequencing data. SMuRF predicts both SNVs and indels with high accuracy in genome or exome-level sequencing data. Furthermore, the method is robust across multiple tested cancer types and predicts low allele frequency variants with high accuracy. In contrast to existing ensemble-based somatic mutation calling approaches, SMuRF works out-of-the-box and is orders of magnitudes faster.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The method is implemented in R and available at https:\/\/github.com\/skandlab\/SMuRF. SMuRF operates as an add-on to the community-developed bcbio-nextgen somatic variant calling pipeline.<\/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\/btz018","type":"journal-article","created":{"date-parts":[[2019,1,8]],"date-time":"2019-01-08T12:58:56Z","timestamp":1546952336000},"page":"3157-3159","source":"Crossref","is-referenced-by-count":25,"title":["SMuRF: portable and accurate ensemble prediction of somatic mutations"],"prefix":"10.1093","volume":"35","author":[{"given":"Weitai","family":"Huang","sequence":"first","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"},{"name":"Graduate School of Integrative Sciences and Engineering, National University of Singapore , Singapore, Singapore"}]},{"given":"Yu Amanda","family":"Guo","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"}]},{"given":"Karthik","family":"Muthukumar","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"}]},{"given":"Probhonjon","family":"Baruah","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"}]},{"given":"Mei Mei","family":"Chang","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"}]},{"given":"Anders","family":"Jacobsen Skanderup","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research, Genome Institute of Singapore Department of Computational and Systems Biology, , Singapore, Singapore"}]}],"member":"286","published-online":{"date-parts":[[2019,1,12]]},"reference":[{"key":"2023062711322188200_btz018-B1","doi-asserted-by":"crossref","first-page":"10001","DOI":"10.1038\/ncomms10001","article-title":"A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing","volume":"6","author":"Alioto","year":"2015","journal-title":"Nat. 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