{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T22:58:16Z","timestamp":1787785096402,"version":"build-2784847793"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T00:00:00Z","timestamp":1637798400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T00:00:00Z","timestamp":1637798400000},"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":["GM128145"],"award-info":[{"award-number":["GM128145"]}],"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":["GM128145"],"award-info":[{"award-number":["GM128145"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018934","name":"Universit\u00e4t Greifswald","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100018934","id-type":"DOI","asserted-by":"crossref"}]}],"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>BRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>TSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-021-04482-0","type":"journal-article","created":{"date-parts":[[2021,11,26]],"date-time":"2021-11-26T01:24:52Z","timestamp":1637889892000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":387,"title":["TSEBRA: transcript selector for BRAKER"],"prefix":"10.1186","volume":"22","author":[{"given":"Lars","family":"Gabriel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharina J.","family":"Hoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom\u00e1\u0161","family":"Br\u016fna","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Borodovsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8696-0384","authenticated-orcid":false,"given":"Mario","family":"Stanke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,25]]},"reference":[{"issue":"D1","key":"4482_CR1","doi-asserted-by":"crossref","first-page":"D92","DOI":"10.1093\/nar\/gkaa1023","volume":"49","author":"EW Sayers","year":"2021","unstructured":"Sayers EW, Cavanaugh M, Clark K, Pruitt KD, Schoch CL, Sherry ST, et al. GenBank. Nucleic Acids Res. 2021;49(D1):D92\u20136.","journal-title":"Nucleic Acids Res."},{"key":"4482_CR2","unstructured":"National Center for Biotechnology Information (NCBI). GenBank eukayotic genome reports; 2021. Accessed 01 May 2021. https:\/\/ftp.ncbi.nlm.nih.gov\/genomes\/GENOME_REPORTS\/."},{"key":"4482_CR3","unstructured":"National Center for Biotechnology Information (NCBI). Eukaryotic Genome Annotation at NCBI; 2021. Accessed 01 May 2021. https:\/\/www.ncbi.nlm.nih.gov\/genome\/annotation_euk\/."},{"issue":"1","key":"4482_CR4","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nrg2484","volume":"10","author":"Z Wang","year":"2009","unstructured":"Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10(1):57\u201363.","journal-title":"Nat. Rev. Genet."},{"key":"4482_CR5","unstructured":"Gremme G. Computational gene structure prediction [dissertation]. Staats-und Universit\u00e4tsbibliothek Hamburg Carl von Ossietzky; 2012."},{"key":"4482_CR6","doi-asserted-by":"crossref","unstructured":"Leinonen R, Sugawara H, Shumway M, Collaboration INSD. The sequence read archive. Nucleic Acids Research. 2010;39(suppl\\_1):D19\u2013D21.","DOI":"10.1093\/nar\/gkq1019"},{"key":"4482_CR7","doi-asserted-by":"crossref","unstructured":"Kriventseva EV, Kuznetsov D, Tegenfeldt F, Manni M, Dias R, Sim\u00e3o FA, et\u00a0al. OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs. Nucleic Acids Res. 2018 11;47(D1):D807\u2013D811.","DOI":"10.1093\/nar\/gky1053"},{"issue":"1","key":"4482_CR8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-15-189","volume":"15","author":"O Gotoh","year":"2014","unstructured":"Gotoh O, Morita M, Nelson DR. Assessment and refinement of eukaryotic gene structure prediction with gene-structure-aware multiple protein sequence alignment. BMC Bioinform. 2014;15(1):1\u201313.","journal-title":"BMC Bioinform."},{"issue":"5","key":"4482_CR9","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1093\/bioinformatics\/btv661","volume":"32","author":"KJ Hoff","year":"2016","unstructured":"Hoff KJ, Lange S, Lomsadze A, Borodovsky M, Stanke M. BRAKER1: unsupervised RNA-Seq-based genome annotation with GeneMark-ET and AUGUSTUS. Bioinformatics. 2016;32(5):767\u20139.","journal-title":"Bioinformatics"},{"issue":"20","key":"4482_CR10","doi-asserted-by":"crossref","first-page":"6494","DOI":"10.1093\/nar\/gki937","volume":"33","author":"A Lomsadze","year":"2005","unstructured":"Lomsadze A, Ter-Hovhannisyan V, Chernoff YO, Borodovsky M. Gene identification in novel eukaryotic genomes by self-training algorithm. Nucleic Acids Res. 2005;33(20):6494\u2013506.","journal-title":"Nucleic Acids Res."},{"issue":"12","key":"4482_CR11","doi-asserted-by":"crossref","first-page":"1979","DOI":"10.1101\/gr.081612.108","volume":"18","author":"V Ter-Hovhannisyan","year":"2008","unstructured":"Ter-Hovhannisyan V, Lomsadze A, Chernoff YO, Borodovsky M. Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res. 2008;18(12):1979\u201390.","journal-title":"Genome Res."},{"issue":"15","key":"4482_CR12","doi-asserted-by":"crossref","first-page":"e119","DOI":"10.1093\/nar\/gku557","volume":"42","author":"A Lomsadze","year":"2014","unstructured":"Lomsadze A, Burns PD, Borodovsky M. Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm. Nucleic Acids Res. 2014;42(15):e119\u2013e119.","journal-title":"Nucleic Acids Res."},{"key":"4482_CR13","doi-asserted-by":"crossref","unstructured":"Stanke M, Steinkamp R, Waack S, Morgenstern B. AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res. 2004;32(suppl\\_2):W309\u201312.","DOI":"10.1093\/nar\/gkh379"},{"issue":"1","key":"4482_CR14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-7-62","volume":"7","author":"M Stanke","year":"2006","unstructured":"Stanke M, Sch\u00f6ffmann O, Morgenstern B, Waack S. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinform. 2006;7(1):1\u201311.","journal-title":"BMC Bioinform."},{"key":"4482_CR15","doi-asserted-by":"crossref","unstructured":"Stanke M, Keller O, Gunduz I, Hayes A, Waack S, Morgenstern B. AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Res. 2006;34(suppl\\_2):W435\u20139.","DOI":"10.1093\/nar\/gkl200"},{"issue":"W1","key":"4482_CR16","doi-asserted-by":"crossref","first-page":"W123","DOI":"10.1093\/nar\/gkt418","volume":"41","author":"KJ Hoff","year":"2013","unstructured":"Hoff KJ, Stanke M. WebAUGUSTUS-a web service for training AUGUSTUS and predicting genes in eukaryotes. Nucleic Acids Res. 2013;41(W1):W123\u20138.","journal-title":"Nucleic Acids Res."},{"issue":"5","key":"4482_CR17","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1093\/bioinformatics\/btn013","volume":"24","author":"M Stanke","year":"2008","unstructured":"Stanke M, Diekhans M, Baertsch R, Haussler D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics. 2008;24(5):637\u201344.","journal-title":"Bioinformatics"},{"key":"4482_CR18","doi-asserted-by":"crossref","unstructured":"Br\u016fna T, Hoff KJ, Lomsadze A, Stanke M, Borodovsky M. BRAKER2: automatic eukaryotic genome annotation with GeneMark-EP+ and AUGUSTUS supported by a protein database. NAR Genomics and Bioinform. 2021;3(1):lqaa108.","DOI":"10.1093\/nargab\/lqaa108"},{"key":"4482_CR19","doi-asserted-by":"crossref","unstructured":"Br\u016fna T, Lomsadze A, Borodovsky M. GeneMark-EP+: eukaryotic gene prediction with self-training in the space of genes and proteins. NAR Genom Bioinform. 2020;2(2):lqaa026.","DOI":"10.1093\/nargab\/lqaa026"},{"issue":"1","key":"4482_CR20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-12-491","volume":"12","author":"C Holt","year":"2011","unstructured":"Holt C, Yandell M. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinform. 2011;12(1):1\u201314.","journal-title":"BMC Bioinform"},{"issue":"1","key":"4482_CR21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-018-2203-5","volume":"19","author":"J Keilwagen","year":"2018","unstructured":"Keilwagen J, Hartung F, Paulini M, Twardziok SO, Grau J. Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi. BMC Bioinform. 2018;19(1):1\u201312.","journal-title":"BMC Bioinform"},{"key":"4482_CR22","doi-asserted-by":"crossref","unstructured":"Banerjee S, Bhandary P, Woodhouse MR, Sen TZ, Wise RP, Andorf CM. FINDER: an automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences. BioRxiv. 2021.","DOI":"10.1101\/2021.02.04.429837"},{"issue":"1","key":"4482_CR23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12864-015-1315-9","volume":"16","author":"F Zickmann","year":"2015","unstructured":"Zickmann F, Renard BY. IPred-integrating ab initio and evidence based gene predictions to improve prediction accuracy. BMC Genom. 2015;16(1):1\u20138.","journal-title":"BMC Genom"},{"issue":"1","key":"4482_CR24","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1101\/gr.1562804","volume":"14","author":"JE Allen","year":"2004","unstructured":"Allen JE, Pertea M, Salzberg SL. Computational gene prediction using multiple sources of evidence. Genome Res. 2004;14(1):142\u20138.","journal-title":"Genome Res"},{"issue":"18","key":"4482_CR25","doi-asserted-by":"crossref","first-page":"3596","DOI":"10.1093\/bioinformatics\/bti609","volume":"21","author":"JE Allen","year":"2005","unstructured":"Allen JE, Salzberg SL. JIGSAW: integration of multiple sources of evidence for gene prediction. Bioinformatics. 2005;21(18):3596\u2013603.","journal-title":"Bioinformatics"},{"issue":"5","key":"4482_CR26","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1093\/bioinformatics\/btn004","volume":"24","author":"Q Liu","year":"2008","unstructured":"Liu Q, Mackey AJ, Roos DS, Pereira FC. Evigan: a hidden variable model for integrating gene evidence for eukaryotic gene prediction. Bioinformatics. 2008;24(5):597\u2013605.","journal-title":"Bioinformatics."},{"key":"4482_CR27","doi-asserted-by":"crossref","unstructured":"Brejov\u00e1 B, Brown DG, Li M, Vina\u0159 T. ExonHunter: a comprehensive approach to gene finding. Bioinformatics. 2005;21(suppl\\_1):i57\u201365.","DOI":"10.1093\/bioinformatics\/bti1040"},{"issue":"1","key":"4482_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/gb-2008-9-1-r1","volume":"9","author":"BJ Haas","year":"2008","unstructured":"Haas BJ, Salzberg SL, Zhu W, Pertea M, Allen JE, Orvis J, et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 2008;9(1):1\u201322.","journal-title":"Genome Biol"},{"issue":"7229","key":"4482_CR29","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1038\/nature07723","volume":"457","author":"AH Paterson","year":"2009","unstructured":"Paterson AH, Bowers JE, Bruggmann R, Dubchak I, Grimwood J, Gundlach H, et al. The Sorghum bicolor genome and the diversification of grasses. Nature. 2009;457(7229):551\u20136.","journal-title":"Nature"},{"key":"4482_CR30","doi-asserted-by":"crossref","unstructured":"Zhang T, Hu Y, Jiang W, Fang L, Guan X, Chen J, et\u00a0al. Sequencing of allotetraploid cotton (Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement. Nat Biotechnol. 2015;33(5):531\u20137.","DOI":"10.1038\/nbt.3207"},{"key":"4482_CR31","unstructured":"Hoff KJ, Br\u016dna T, Lomsadze A, Stanke M, Borodovsky M. Fully Automated and Accurate Annotation of Eukaryotic Genomes with BRAKER2. Poster presented at: Plant and Animal Genome XXVIII Conference; 2020."},{"key":"4482_CR32","doi-asserted-by":"crossref","unstructured":"Hoff KJ, Lomsadze A, Borodovsky M, Stanke M. Whole-genome annotation with BRAKER. In: Gene Prediction. Springer; 2019. p. 65\u201395.","DOI":"10.1007\/978-1-4939-9173-0_5"},{"issue":"1","key":"4482_CR33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-019-3182-x","volume":"20","author":"M Stanke","year":"2019","unstructured":"Stanke M, Bruhn W, Becker F, Hoff KJ. VARUS: sampling complementary RNA reads from the sequence read archive. BMC Bioinform. 2019;20(1):1\u20137.","journal-title":"BMC Bioinform."},{"issue":"8","key":"4482_CR34","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1038\/s41587-019-0201-4","volume":"37","author":"D Kim","year":"2019","unstructured":"Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37(8):907\u201315.","journal-title":"Nat Biotechnol"},{"issue":"2","key":"4482_CR35","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/BF02295996","volume":"12","author":"Q McNemar","year":"1947","unstructured":"McNemar Q. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika. 1947;12(2):153\u20137.","journal-title":"Psychometrika"},{"issue":"302","key":"4482_CR36","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1080\/14786440009463897","volume":"50","author":"KX Pearson","year":"1900","unstructured":"Pearson KX. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Lond Edinburgh Dublin Philos Mag J Sci. 1900;50(302):157\u201375.","journal-title":"Lond Edinburgh Dublin Philos Mag J Sci"},{"key":"4482_CR37","unstructured":"Haas BJ, Salzberg SL, Zhu W, Pertea M, Allen. EvidenceModeler. GitHub; 2020. https:\/\/github.com\/EVidenceModeler\/EVidenceModeler\/tree\/68e724ea25badcd74a1d4631c712605a4efa78ef."},{"issue":"1","key":"4482_CR38","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/nmeth.3176","volume":"12","author":"B Buchfink","year":"2015","unstructured":"Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12(1):59\u201360.","journal-title":"Nat Methods"},{"issue":"7","key":"4482_CR39","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1038\/nbt.1883","volume":"29","author":"MG Grabherr","year":"2011","unstructured":"Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat Biotechnol. 2011;29(7):644.","journal-title":"Nat Biotechnol"},{"issue":"19","key":"4482_CR40","doi-asserted-by":"crossref","first-page":"5654","DOI":"10.1093\/nar\/gkg770","volume":"31","author":"BJ Haas","year":"2003","unstructured":"Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK Jr, Hannick LI, et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003;31(19):5654\u201366.","journal-title":"Nucleic Acids Res"},{"issue":"20","key":"4482_CR41","doi-asserted-by":"crossref","first-page":"E4700","DOI":"10.1073\/pnas.1721395115","volume":"115","author":"R van Velzen","year":"2018","unstructured":"van Velzen R, Holmer R, Bu F, Rutten L, van Zeijl A, Liu W, et al. Comparative genomics of the nonlegume Parasponia reveals insights into evolution of nitrogen-fixing rhizobium symbioses. Proc Natl Acad Sci. 2018;115(20):E4700\u20139.","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"4482_CR42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-018-07882-8","volume":"10","author":"L Hu","year":"2019","unstructured":"Hu L, Xu Z, Wang M, Fan R, Yuan D, Wu B, et al. The chromosome-scale reference genome of black pepper provides insight into piperine biosynthesis. Nat Commun. 2019;10(1):1\u201311.","journal-title":"Nat Commun"},{"key":"4482_CR43","unstructured":"Seetharam A, Singh U, Li J, Bhandary P, Arendsee Z, Wurtele ES. Maximizing prediction of orphan genes in assembled genomes. BioRxiv. 2019;."},{"issue":"1","key":"4482_CR44","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1111\/1755-0998.13259","volume":"21","author":"J Lee","year":"2021","unstructured":"Lee J, Nishiyama T, Shigenobu S, Yamaguchi K, Suzuki Y, Shimada T, et al. The genome sequence of Samia ricini, a new model species of lepidopteran insect. Mol Ecol Resour. 2021;21(1):327\u201339.","journal-title":"Mol Ecol Resour"},{"issue":"1","key":"4482_CR45","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1186\/s12870-018-1282-9","volume":"18","author":"M Jayakodi","year":"2018","unstructured":"Jayakodi M, Choi BS, Lee SC, Kim NH, Park JY, Jang W, et al. Ginseng Genome Database: an open-access platform for genomics of Panax ginseng. BMC Plant Biol. 2018;18(1):62.","journal-title":"BMC Plant Biol"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-021-04482-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-021-04482-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-021-04482-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T13:33:45Z","timestamp":1638279225000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-021-04482-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,25]]},"references-count":45,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["4482"],"URL":"https:\/\/doi.org\/10.1186\/s12859-021-04482-0","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.06.07.447316","asserted-by":"object"}]},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,25]]},"assertion":[{"value":"4 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 November 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"566"}}