{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T10:08:57Z","timestamp":1784110137706,"version":"3.55.0"},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T00:00:00Z","timestamp":1605571200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T00:00:00Z","timestamp":1605571200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004440","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["202778\/B\/16\/Z"],"award-info":[{"award-number":["202778\/B\/16\/Z"]}],"id":[{"id":"10.13039\/100004440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004440","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["202778\/Z\/16\/Z"],"award-info":[{"award-number":["202778\/Z\/16\/Z"]}],"id":[{"id":"10.13039\/100004440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004440","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["105104\/Z\/14\/Z"],"award-info":[{"award-number":["105104\/Z\/14\/Z"]}],"id":[{"id":"10.13039\/100004440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","award":["A22909"],"award-info":[{"award-number":["A22909"]}],"id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","award":["A19771"],"award-info":[{"award-number":["A19771"]}],"id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/P000789\/1"],"award-info":[{"award-number":["MR\/P000789\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["NCI U54 CA217376"],"award-info":[{"award-number":["NCI U54 CA217376"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n<jats:title>Background<\/jats:title>\n<jats:p>The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>In a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusions<\/jats:title>\n<jats:p>We present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities.<\/jats:p>\n<\/jats:sec>","DOI":"10.1186\/s12859-020-03863-1","type":"journal-article","created":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T18:02:58Z","timestamp":1605636178000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4240-3265","authenticated-orcid":false,"given":"Giulio","family":"Caravagna","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guido","family":"Sanguinetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trevor A.","family":"Graham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Sottoriva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,17]]},"reference":[{"issue":"22","key":"3863_CR1","doi-asserted-by":"publisher","first-page":"2109","DOI":"10.1056\/NEJMoa1616288","volume":"376","author":"M Jamal-Hanjani","year":"2017","unstructured":"Jamal-Hanjani M, et al. Tracking the evolution of non-small-cell lung cancer. NEJM. 2017;376(22):2109\u201321.","journal-title":"NEJM"},{"issue":"3","key":"3863_CR2","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1093\/annonc\/mdy506","volume":"30","author":"I Spiteri","year":"2019","unstructured":"Spiteri I, et al. Evolutionary dynamics of residual disease in human glioblastoma. Ann Oncol. 2019;30(3):456\u201363.","journal-title":"Ann Oncol"},{"issue":"28","key":"3863_CR3","doi-asserted-by":"publisher","first-page":"E4025-E403415.9","DOI":"10.1073\/pnas.1520213113","volume":"113","author":"G Caravagna","year":"2016","unstructured":"Caravagna G, et al. Algorithmic methods to infer the evolutionary trajectories in cancer progression. PNAS. 2016;113(28):E4025-E403415.9.","journal-title":"PNAS"},{"issue":"9","key":"3863_CR4","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1038\/s41592-018-0108-x","volume":"15","author":"G Caravagna","year":"2018","unstructured":"Caravagna G, et al. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nat Methods. 2018;15(9):707\u201314.","journal-title":"Nat Methods"},{"issue":"3","key":"3863_CR5","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1016\/j.cell.2018.03.043","volume":"173","author":"S Turajlic","year":"2018","unstructured":"Turajlic S, et al. Deterministic evolutionary trajectories influence primary tumor growth: TRACERx renal. Cell. 2018a;173(3):595\u2013610.","journal-title":"Cell"},{"issue":"3","key":"3863_CR6","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1016\/j.cell.2018.03.057","volume":"173","author":"S Turajlic","year":"2018","unstructured":"Turajlic S, et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx renal. Cell. 2018b;173(3):581\u201394.","journal-title":"Cell"},{"issue":"5","key":"3863_CR7","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1016\/j.cell.2012.04.023","volume":"149","author":"S Nik-Zainal","year":"2012","unstructured":"Nik-Zainal S, et al. The life history of 21 breast cancers. Cell. 2012;149(5):994\u20131007.","journal-title":"Cell"},{"issue":"7","key":"3863_CR8","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1038\/s41576-019-0114-6","volume":"20","author":"S Turajlic","year":"2019","unstructured":"Turajlic S, et al. Resolving genetic heterogeneity in cancer. Nat Rev Genet. 2019;20(7):404\u201316.","journal-title":"Nat Rev Genet"},{"key":"3863_CR9","doi-asserted-by":"publisher","first-page":"898","DOI":"10.1038\/s41588-020-0675-5","volume":"52","author":"G Caravagna","year":"2020","unstructured":"Caravagna G, et al. Subclonal reconstruction of tumors by using machine learning and population genetics. Nat Genet. 2020;52:898\u2013907.","journal-title":"Nat Genet."},{"issue":"3","key":"3863_CR10","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1038\/ng.3214","volume":"47","author":"A Sottoriva","year":"2015","unstructured":"Sottoriva A, et al. A Big Bang model of human colorectal tumor growth. Nat Genet. 2015;47(3):209.","journal-title":"Nat Genet"},{"issue":"3","key":"3863_CR11","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1038\/ng.3489","volume":"48","author":"MJ Williams","year":"2016","unstructured":"Williams MJ, et al. Identification of neutral tumor evolution across cancer types. Nat Genet. 2016;48(3):238.","journal-title":"Nat Genet"},{"issue":"6","key":"3863_CR12","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1038\/s41588-018-0128-6","volume":"50","author":"MJ Williams","year":"2018","unstructured":"Williams MJ, et al. Quantification of subclonal selection in cancer from bulk sequencing data. Nat Genet. 2018;50(6):895\u2013903.","journal-title":"Nat Genet"},{"issue":"29","key":"3863_CR13","doi-asserted-by":"publisher","first-page":"11682","DOI":"10.1073\/pnas.1309667110","volume":"110","author":"DA Kessler","year":"2013","unstructured":"Kessler DA, Levine H. Large population solution of the stochastic Luria-Delbr\u00fcck evolution model. Proc Natl Acad Sci. 2013;110(29):11682\u20137.","journal-title":"Proc Natl Acad Sci"},{"key":"3863_CR14","unstructured":"Efron B. The jackknife, the bootstrap and other resampling plans. In: CBMS-NSF regional conference series in applied mathematics; SIAM, 1982. ISBN 978-0-89871-179-0, p. xi + 85."},{"issue":"5","key":"3863_CR15","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1016\/j.cell.2017.09.042","volume":"171","author":"I Martincorena","year":"2017","unstructured":"Martincorena I, et al. Universal patterns of selection in cancer and somatic tissues. Cell. 2017;171(5):1029\u201341.","journal-title":"Cell"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03863-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03863-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03863-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T18:04:52Z","timestamp":1605636292000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03863-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,17]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["3863"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03863-1","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,17]]},"assertion":[{"value":"7 August 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Does not apply since we use public data.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Does not apply.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"All the authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"531"}}