{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:52:27Z","timestamp":1740135147029,"version":"3.37.3"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"S6","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T00:00:00Z","timestamp":1605657600000},"content-version":"vor","delay-in-days":17,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61732009"],"award-info":[{"award-number":["61732009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>DNA methylation in the human genome is acknowledged to be widely associated with biological processes and complex diseases. The Illumina Infinium methylation arrays have been approved as one of the most efficient and universal technologies to investigate the whole genome changes of methylation patterns. As methylation arrays may still be the dominant method for detecting methylation in the anticipated future, it is crucial to develop a reliable workflow to analysis methylation array data.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this study, we develop a web service MADA for the whole process of methylation arrays data analysis, which includes the steps of a comprehensive differential methylation analysis pipeline: pre-processing (data loading, quality control, data filtering, and normalization), batch effect correction, differential methylation analysis, and downstream analysis. In addition, we provide the visualization of pre-processing, differentially methylated probes or regions, gene ontology, pathway and cluster analysis results. Moreover, a customization function for users to define their own workflow is also provided in MADA.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>With the analysis of two case studies, we have shown that MADA can complete the whole procedure of methylation array data analysis. MADA provides a graphical user interface and enables users with no computational skills and limited bioinformatics background to carry on complicated methylation array data analysis. The web server is available at: <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/120.24.94.89:8080\/MADA\">http:\/\/120.24.94.89:8080\/MADA<\/jats:ext-link><\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-020-03734-9","type":"journal-article","created":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T04:14:07Z","timestamp":1605672847000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["MADA: a web service for analysing DNA methylation array data"],"prefix":"10.1186","volume":"21","author":[{"given":"Xinyu","family":"Hu","sequence":"first","affiliation":[]},{"given":"Li","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Linconghua","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Fang-Xiang","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0188-1394","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,18]]},"reference":[{"issue":"4","key":"3734_CR1","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1038\/nrc1045","volume":"3","author":"PW Laird","year":"2003","unstructured":"Laird PW. Early detection: the power and the promise of DNA methylation markers. Nat Rev Cancer. 2003;3(4):253.","journal-title":"Nat Rev Cancer"},{"issue":"7732","key":"3734_CR2","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1038\/s41586-018-0703-0","volume":"563","author":"SY Shen","year":"2018","unstructured":"Shen SY, Singhania R, Fehringer G, et al. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature. 2018;563(7732):579.","journal-title":"Nature"},{"issue":"7697","key":"3734_CR3","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1038\/nature26000","volume":"555","author":"D Capper","year":"2018","unstructured":"Capper D, Jones DT, Sill M, Hovestadt V, Schrimpf D, Sturm D, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697):469.","journal-title":"Nature"},{"issue":"3","key":"3734_CR4","doi-asserted-by":"publisher","first-page":"32928","DOI":"10.1371\/journal.pone.0032928","volume":"7","author":"M Teng","year":"2012","unstructured":"Teng M, Balch C, Liu Y, Li M, Huang TH, Wang Y, et al. The influence of cis-regulatory elements on dna methylation fidelity. PLoS One. 2012;7(3):32928.","journal-title":"PLoS One"},{"issue":"4","key":"3734_CR5","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1016\/j.ygeno.2011.07.007","volume":"98","author":"M Bibikova","year":"2011","unstructured":"Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM. High density DNA methylation array with single CpG site resolution. Genomics. 2011;98(4):288\u201395.","journal-title":"Genomics"},{"issue":"2","key":"3734_CR6","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1038\/ng.298","volume":"41","author":"RA Irizarry","year":"2009","unstructured":"Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, et al. The human colon cancer methylome shows similar hypo-and hypermethylation at conserved tissue-specific cpg island shores. Nat Genet. 2009;41(2):178\u201386.","journal-title":"Nat Genet"},{"issue":"10","key":"3734_CR7","doi-asserted-by":"publisher","first-page":"1363","DOI":"10.1093\/bioinformatics\/btu049","volume":"30","author":"MJ Aryee","year":"2014","unstructured":"Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30(10):1363\u20139.","journal-title":"Bioinformatics"},{"issue":"3","key":"3734_CR8","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1093\/bioinformatics\/btt684","volume":"30","author":"TJ Morris","year":"2013","unstructured":"Morris TJ, Butcher LM, Feber A, Teschendorff AE, Chakravarthy AR, Wojdacz. ChAMP: 450k chip analysis methylation pipeline. Bioinformatics. 2013;30(3):428\u201330.","journal-title":"Bioinformatics"},{"key":"3734_CR9","doi-asserted-by":"publisher","unstructured":"Li M, Tang L, Wu F-X, Pan Y, Wang J. CSA: a web service for ChIP-Seq analysis. BMC Bioinformatics. 2019. https:\/\/doi.org\/10.1186\/s12859-019-3090-0.","DOI":"10.1186\/s12859-019-3090-0"},{"key":"3734_CR10","doi-asserted-by":"publisher","unstructured":"Zhang J, Zeng M, Kurgan L, Wu F-X, Li M. NetEPD: a network-based essential protein discovery platform. Tsinghua Sci Technol. 2019. https:\/\/doi.org\/10.26599\/TST.2019.9010056.","DOI":"10.26599\/TST.2019.9010056"},{"issue":"1","key":"3734_CR11","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1186\/s13072-015-0045-1","volume":"8","author":"J Preussner","year":"2015","unstructured":"Preussner J, Bayer J, Kuenne C, Looso M. ADMIRE: analysis and visualization of differential methylation in genomic regions using the Infinium HumanMethylation450 assay. Epigenetics Chromatin. 2015;8(1):51.","journal-title":"Epigenetics Chromatin"},{"issue":"2","key":"3734_CR12","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1093\/bioinformatics\/bts680","volume":"29","author":"AE Teschendorff","year":"2012","unstructured":"Teschendorff AE, Marabita F, Lechner M, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2012;29(2):189\u201396.","journal-title":"Bioinformatics"},{"issue":"6","key":"3734_CR13","doi-asserted-by":"publisher","first-page":"771","DOI":"10.2217\/epi.11.105","volume":"3","author":"S Dedeurwaerder","year":"2011","unstructured":"Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. Evaluation of the Infinium methylation 450K technology. Epigenomics. 2011;3(6):771\u201384.","journal-title":"Epigenomics"},{"issue":"6","key":"3734_CR14","doi-asserted-by":"publisher","first-page":"R44","DOI":"10.1186\/gb-2012-13-6-r44","volume":"13","author":"J Maksimovic","year":"2012","unstructured":"Maksimovic J, Gordon L, Oshlack A. SWAN: subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol. 2012;13(6):R44.","journal-title":"Genome Biol"},{"issue":"11","key":"3734_CR15","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1186\/s13059-014-0503-2","volume":"15","author":"JP Fortin","year":"2014","unstructured":"Fortin JP, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, et al. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 2014;15(11):503.","journal-title":"Genome Biol"},{"issue":"7","key":"3734_CR16","doi-asserted-by":"publisher","first-page":"e90","DOI":"10.1093\/nar\/gkt090","volume":"41","author":"TJ Triche Jr","year":"2013","unstructured":"Triche TJ Jr, Weisenberger DJ, Van Den Berg D, Laird PW, Siegmund KD. Low-level processing of Illumina Infinium DNA methylation beadarrays. Nucleic Acids Res. 2013;41(7):e90.","journal-title":"Nucleic Acids Res"},{"issue":"3","key":"3734_CR17","doi-asserted-by":"publisher","first-page":"325","DOI":"10.2217\/epi.12.21","volume":"4","author":"N Touleimat","year":"2012","unstructured":"Touleimat N, Tost J. Complete pipeline for Infinium human methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation. Epigenomics. 2012;4(3):325\u201341.","journal-title":"Epigenomics"},{"issue":"1","key":"3734_CR18","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1186\/1471-2164-14-293","volume":"14","author":"R Pidsley","year":"2013","unstructured":"Pidsley R, Wong CC, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics. 2013;14(1):293.","journal-title":"BMC Genomics"},{"issue":"2","key":"3734_CR19","doi-asserted-by":"publisher","first-page":"203","DOI":"10.4161\/epi.23470","volume":"8","author":"YA Chen","year":"2013","unstructured":"Chen YA, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics. 2013;8(2):203\u20139.","journal-title":"Epigenetics"},{"issue":"48","key":"3734_CR20","doi-asserted-by":"publisher","first-page":"18718","DOI":"10.1073\/pnas.0808709105","volume":"105","author":"JT Leek","year":"2008","unstructured":"Leek JT, Storey JD. A general framework for multiple testing dependence. Proc Natl Acad Sci. 2008;105(48):18718\u201323.","journal-title":"Proc Natl Acad Sci"},{"key":"3734_CR21","first-page":"397","volume-title":"Linear models for microarray data. Bioinformatics & Computational Biology Solutions Using R & bioconductor","author":"G Smyth","year":"2011","unstructured":"Smyth G, Limma K. Linear models for microarray data. Bioinformatics & Computational Biology Solutions Using R & bioconductor; 2011. p. 397\u2013420."},{"issue":"9","key":"3734_CR22","doi-asserted-by":"publisher","first-page":"5116","DOI":"10.1073\/pnas.091062498","volume":"98","author":"VG Tusher","year":"2001","unstructured":"Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response [J]. Proc Natl Acad Sci. 2001;98(9):5116\u201321.","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"3734_CR23","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/1756-8935-8-6","volume":"8","author":"TJ Peters","year":"2015","unstructured":"Peters TJ, Buckley MJ, Statham AL, Pidsley R, Samaras K, Lord RV, et al. De novo identification of differentially methylated regions in the human genome. Epigenetics Chromatin. 2015;8(1):6.","journal-title":"Epigenetics Chromatin"},{"issue":"1","key":"3734_CR24","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1093\/ije\/dyr238","volume":"41","author":"AE Jaffe","year":"2012","unstructured":"Jaffe AE, Murakami P, Lee H, Leek JT, Fallin MD, Feinberg AP, et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int J Epidemiol. 2012;41(1):200\u20139.","journal-title":"Int J Epidemiol"},{"key":"3734_CR25","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.ymeth.2014.10.036","volume":"72","author":"LM Butcher","year":"2015","unstructured":"Butcher LM, Beck S. Probe lasso: a novel method to rope in differentially methylated regions with 450K DNA methylation data. Methods. 2015;72:21\u20138.","journal-title":"Methods"},{"issue":"17","key":"3734_CR26","doi-asserted-by":"publisher","first-page":"2604","DOI":"10.1093\/bioinformatics\/btw304","volume":"32","author":"R Kolde","year":"2016","unstructured":"Kolde R, M\u00e4rtens K, Lokk K, Laur S, Vilo J. Seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data. Bioinformatics. 2016;32(17):2604\u201310.","journal-title":"Bioinformatics"},{"issue":"2","key":"3734_CR27","doi-asserted-by":"publisher","first-page":"R14","DOI":"10.1186\/gb-2010-11-2-r14","volume":"11","author":"MD Young","year":"2010","unstructured":"Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11(2):R14.","journal-title":"Genome Biol"},{"issue":"2","key":"3734_CR28","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1093\/bioinformatics\/btv560","volume":"32","author":"B Phipson","year":"2015","unstructured":"Phipson B, Maksimovic J, Oshlack A. missMethyl: R package for analyzing data from Illumina\u2019s HumanMethylation450 platform. Bioinformatics. 2015;32(2):286\u20138.","journal-title":"Bioinformatics"},{"issue":"1","key":"3734_CR29","doi-asserted-by":"publisher","first-page":"3916","DOI":"10.1038\/s41598-017-03682-0","volume":"7","author":"V Kukushkina","year":"2017","unstructured":"Kukushkina V, Modhukur V, Suhorut\u0161enko M, Peters M, M\u00e4gi R, Rahmioglu N, et al. DNA methylation changes in endometrium and correlation with gene expression during the transition from pre-receptive to receptive phase. Sci Rep. 2017;7(1):3916.","journal-title":"Sci Rep"},{"issue":"Database issue","key":"3734_CR30","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1093\/nar\/gkq1184","volume":"39","author":"T Barrett","year":"2011","unstructured":"Barrett T, Troup DB, Wilhite SE, Ledoux P, Evangelista C, Kim IF, et al. Ncbi geo: archive for functional genomics data sets\u201410 years on. Nucleic Acids Res. 2011;39(Database issue):1005\u201310.","journal-title":"Nucleic Acids Res"},{"issue":"1","key":"3734_CR31","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1186\/s13148-017-0389-4","volume":"9","author":"T Guastafierro","year":"2017","unstructured":"Guastafierro T, Bacalini MG, Marcoccia A, Gentilini D, Pisoni S, Blasio AMD, et al. Genome-wide dna methylation analysis in blood cells from patients with werner syndrome. Clin Epigenetics. 2017;9(1):92.","journal-title":"Clin Epigenetics"},{"issue":"11","key":"3734_CR32","doi-asserted-by":"publisher","first-page":"1138","DOI":"10.1038\/nmeth.3115","volume":"11","author":"Y Assenov","year":"2014","unstructured":"Assenov Y, M\u00fcller F, Lutsik P, Walter J, Lengauer T, Bock C. Comprehensive analysis of DNA methylation data with RnBeads. Nat Methods. 2014;11(11):1138.","journal-title":"Nat Methods"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03734-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03734-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03734-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,21]],"date-time":"2020-11-21T06:03:10Z","timestamp":1605938590000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03734-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11]]},"references-count":32,"journal-issue":{"issue":"S6","published-print":{"date-parts":[[2020,11]]}},"alternative-id":["3734"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03734-9","relation":{},"ISSN":["1471-2105"],"issn-type":[{"type":"electronic","value":"1471-2105"}],"subject":[],"published":{"date-parts":[[2020,11]]},"assertion":[{"value":"15 August 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"403"}}