{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:34:22Z","timestamp":1762508062442,"version":"3.37.3"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,3,17]],"date-time":"2020-03-17T00:00:00Z","timestamp":1584403200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"German Ministry of Education and Research","award":["FKZ031L0080"],"award-info":[{"award-number":["FKZ031L0080"]}]},{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100004807","name":"DFG","doi-asserted-by":"publisher","award":["CIBSS-EXC-2189-2100249960-390939984"],"award-info":[{"award-number":["CIBSS-EXC-2189-2100249960-390939984"]}],"id":[{"id":"10.13039\/100004807","id-type":"DOI","asserted-by":"publisher"}]},{"name":"EU Horizon 2020 program"},{"name":"Marie Sk\u0142odowska-Curie","award":["764965"],"award-info":[{"award-number":["764965"]}]},{"name":"European Research Area Network for Coordinating Action in Plant Sciences"},{"name":"ERA-CAPS"},{"name":"Austrian Science","award":["FWFI3979"],"award-info":[{"award-number":["FWFI3979"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Bisulfite sequencing (BS-seq) is a state-of-the-art technique for investigating methylation of the DNA to gain insights into the epigenetic regulation. Several algorithms have been published for identification of differentially methylated regions (DMRs). However, the performances of the individual methods remain unclear and it is difficult to optimally select an algorithm in application settings.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We analyzed BS-seq data from four plants covering three taxonomic groups. We first characterized the data using multiple summary statistics describing methylation levels, coverage, noise, as well as frequencies, magnitudes and lengths of methylated regions. Then, simulated datasets with most similar characteristics to real experimental data were created. Seven different algorithms (metilene, methylKit, MOABS, DMRcate, Defiant, BSmooth, MethylSig) for DMR identification were applied and their performances were assessed. A blind and independent study design was chosen to reduce bias and to derive practical method selection guidelines. Overall, metilene had superior performance in most settings. Data attributes, such as coverage and spread of the DMR lengths, were found to be useful for selecting the best method for DMR detection. A decision tree to select the optimal approach based on these data attributes is provided. The presented procedure might serve as a general strategy for deriving algorithm selection rules tailored to demands in specific application settings.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Scripts that were used for the analyses and that can be used for prediction of the optimal algorithm are provided at https:\/\/github.com\/kreutz-lab\/DMR-DecisionTree. Simulated and experimental data are available at https:\/\/doi.org\/10.6084\/m9.figshare.11619045.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Contact<\/jats:title>\n                  <jats:p>ckreutz@imbi.uni-freiburg.de<\/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\/btaa191","type":"journal-article","created":{"date-parts":[[2020,3,13]],"date-time":"2020-03-13T12:36:35Z","timestamp":1584102995000},"page":"3314-3321","source":"Crossref","is-referenced-by-count":9,"title":["A blind and independent benchmark study for detecting differentially methylated regions in plants"],"prefix":"10.1093","volume":"36","author":[{"given":"Clemens","family":"Kreutz","sequence":"first","affiliation":[{"name":"Faculty of Medicine and Medical Center , Institute of Medical Biometry and Statistics, University of Freiburg, 79104 Freiburg, Germany"},{"name":"Centre for Integrative Biological Signalling Studies (CIBSS) , University of Freiburg, 79104 Freiburg, Germany"}]},{"given":"Nilay S","family":"Can","sequence":"additional","affiliation":[{"name":"Plant Cell Biology , Faculty of Biology, University of Marburg, 35043 Marburg, Germany"}]},{"given":"Ralf Schulze","family":"Bruening","sequence":"additional","affiliation":[{"name":"Plant Cell Biology , Faculty of Biology, University of Marburg, 35043 Marburg, Germany"}]},{"given":"Rabea","family":"Meyberg","sequence":"additional","affiliation":[{"name":"Plant Cell Biology , Faculty of Biology, University of Marburg, 35043 Marburg, Germany"}]},{"given":"Zsuzsanna","family":"M\u00e9rai","sequence":"additional","affiliation":[{"name":"Gregor Mendel Institute of Molecular Plant Biology , Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria"}]},{"given":"Noe","family":"Fernandez-Pozo","sequence":"additional","affiliation":[{"name":"Plant Cell Biology , Faculty of Biology, University of Marburg, 35043 Marburg, Germany"}]},{"given":"Stefan A","family":"Rensing","sequence":"additional","affiliation":[{"name":"Plant Cell Biology , Faculty of Biology, University of Marburg, 35043 Marburg, Germany"},{"name":"Centre for Biological Signaling Studies (BIOSS) , University of Freiburg, 79104 Freiburg, Germany"}]}],"member":"286","published-online":{"date-parts":[[2020,3,17]]},"reference":[{"key":"2023062312020033600_btaa191-B1","doi-asserted-by":"crossref","first-page":"R87","DOI":"10.1186\/gb-2012-13-10-r87","article-title":"methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles","volume":"13","author":"Akalin","year":"2012","journal-title":"Genome Biol"},{"key":"2023062312020033600_btaa191-B2","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1093\/bioinformatics\/btu142","article-title":"Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data","volume":"30","author":"Akman","year":"2014","journal-title":"Bioinformatics"},{"key":"2023062312020033600_btaa191-B3","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1038\/nmeth.3115","article-title":"Comprehensive analysis of DNA methylation data with RnBeads","volume":"11","author":"Assenov","year":"2014","journal-title":"Nat. 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