{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T08:21:25Z","timestamp":1775809285593,"version":"3.50.1"},"reference-count":51,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2019,1,22]],"date-time":"2019-01-22T00:00:00Z","timestamp":1548115200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000048","name":"American Cancer Society","doi-asserted-by":"publisher","award":["IRG-14-192-40"],"award-info":[{"award-number":["IRG-14-192-40"]}],"id":[{"id":"10.13039\/100000048","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["T32ES007334"],"award-info":[{"award-number":["T32ES007334"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"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>Motivation<\/jats:title>\n                  <jats:p>With the development of chromatin conformation capture technology and its high-throughput derivative Hi-C sequencing, studies of the three-dimensional interactome of the genome that involve multiple Hi-C datasets are becoming available. To account for the technology-driven biases unique to each dataset, there is a distinct need for methods to jointly normalize multiple Hi-C datasets. Previous attempts at removing biases from Hi-C data have made use of techniques which normalize individual Hi-C datasets, or, at best, jointly normalize two datasets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Here, we present multiHiCcompare, a cyclic loess regression-based joint normalization technique for removing biases across multiple Hi-C datasets. In contrast to other normalization techniques, it properly handles the Hi-C-specific decay of chromatin interaction frequencies with the increasing distance between interacting regions. multiHiCcompare uses the general linear model framework for comparative analysis of multiple Hi-C datasets, adapted for the Hi-C-specific decay of chromatin interaction frequencies. multiHiCcompare outperforms other methods when detecting a priori known chromatin interaction differences from jointly normalized datasets. Applied to the analysis of auxin-treated versus\u00a0untreated experiments, and CTCF depletion experiments, multiHiCcompare was able to recover the expected epigenetic and gene expression signatures of loss of chromatin interactions and reveal novel insights.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>multiHiCcompare is freely available on GitHub and as a Bioconductor R package https:\/\/bioconductor.org\/packages\/multiHiCcompare.<\/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\/btz048","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T20:13:29Z","timestamp":1547756009000},"page":"2916-2923","source":"Crossref","is-referenced-by-count":81,"title":["multiHiCcompare: joint normalization and comparative analysis of complex Hi-C experiments"],"prefix":"10.1093","volume":"35","author":[{"given":"John C","family":"Stansfield","sequence":"first","affiliation":[{"name":"Virginia Commonwealth University Department of Biostatistics, , Richmond, VA, USA"}]},{"given":"Kellen G","family":"Cresswell","sequence":"additional","affiliation":[{"name":"Virginia Commonwealth University Department of Biostatistics, , Richmond, VA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0086-8358","authenticated-orcid":false,"given":"Mikhail G","family":"Dozmorov","sequence":"additional","affiliation":[{"name":"Virginia Commonwealth University Department of Biostatistics, , Richmond, VA, USA"}]}],"member":"286","published-online":{"date-parts":[[2019,1,22]]},"reference":[{"key":"2023062711301143200_btz048-B1","doi-asserted-by":"crossref","first-page":"R106.","DOI":"10.1186\/gb-2010-11-10-r106","article-title":"Differential expression analysis for sequence count data","volume":"11","author":"Anders","year":"2010","journal-title":"Genome Biol"},{"key":"2023062711301143200_btz048-B2","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1534\/genetics.110.114983","article-title":"Statistical design and analysis of RNA sequencing data","volume":"185","author":"Auer","year":"2010","journal-title":"Genetics"},{"key":"2023062711301143200_btz048-B3","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1093\/bioinformatics\/btg173","article-title":"Differential expression in sage: accounting for normal between-library variation","volume":"19","author":"Baggerly","year":"2003","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B4","doi-asserted-by":"crossref","first-page":"144.","DOI":"10.1186\/1471-2105-5-144","article-title":"Overdispersed logistic regression for sage: modelling multiple groups and covariates","volume":"5","author":"Baggerly","year":"2004","journal-title":"BMC Bioinformatics"},{"key":"2023062711301143200_btz048-B5","doi-asserted-by":"crossref","first-page":"2778","DOI":"10.1093\/bioinformatics\/bth327","article-title":"Faster cyclic loess: normalizing RNA arrays via linear models","volume":"20","author":"Ballman","year":"2004","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B6","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.cell.2017.09.043","article-title":"Multiscale 3D genome rewiring during mouse neural development","volume":"171","author":"Bonev","year":"2017","journal-title":"Cell"},{"key":"2023062711301143200_btz048-B7","doi-asserted-by":"crossref","first-page":"1306","DOI":"10.1126\/science.1067799","article-title":"Capturing chromosome conformation","volume":"295","author":"Dekker","year":"2002","journal-title":"Science"},{"key":"2023062711301143200_btz048-B8","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1038\/nature14222","article-title":"Chromatin architecture reorganization during stem cell differentiation","volume":"518","author":"Dixon","year":"2015","journal-title":"Nature"},{"key":"2023062711301143200_btz048-B9","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1101\/gr.212241.116","article-title":"FIND: difFerential chromatin interactions detection using a spatial Poisson process","volume":"28","author":"Djekidel","year":"2018","journal-title":"Genome Res"},{"key":"2023062711301143200_btz048-B10","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.cell.2014.09.030","article-title":"Control of cell identity genes occurs in insulated neighborhoods in mammalian chromosomes","volume":"159","author":"Dowen","year":"2014","journal-title":"Cell"},{"key":"2023062711301143200_btz048-B11","doi-asserted-by":"crossref","first-page":"e12657","DOI":"10.1371\/journal.pone.0012657","article-title":"A comprehensive and universal method for assessing the performance of differential gene expression analyses","volume":"5","author":"Dozmorov","year":"2010","journal-title":"PLoS One"},{"key":"2023062711301143200_btz048-B12","first-page":"111","article-title":"Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments","volume":"12","author":"Dudoit","year":"2002","journal-title":"Stat. Sin"},{"key":"2023062711301143200_btz048-B13","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.cels.2016.07.002","article-title":"Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments","volume":"3","author":"Durand","year":"2016","journal-title":"Cell Syst"},{"key":"2023062711301143200_btz048-B14","doi-asserted-by":"crossref","first-page":"20259","DOI":"10.1074\/jbc.M209511200","article-title":"The cohesin SMC3 is a target the for beta-catenin\/TCF4 transactivation pathway","volume":"278","author":"Ghiselli","year":"2003","journal-title":"J. Biol. Chem"},{"key":"2023062711301143200_btz048-B15","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1038\/nbt.1910","article-title":"Sequencing technology does not eliminate biological variability","volume":"29","author":"Hansen","year":"2011","journal-title":"Nat. Biotechnol"},{"key":"2023062711301143200_btz048-B16","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.molcel.2010.05.004","article-title":"Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities","volume":"38","author":"Heinz","year":"2010","journal-title":"Mol.Cell"},{"key":"2023062711301143200_btz048-B17","doi-asserted-by":"crossref","first-page":"1454","DOI":"10.1126\/science.aad9024","article-title":"Activation of proto-oncogenes by disruption of chromosome neighborhoods","volume":"351","author":"Hnisz","year":"2016","journal-title":"Science"},{"key":"2023062711301143200_btz048-B18","doi-asserted-by":"crossref","first-page":"3131","DOI":"10.1093\/bioinformatics\/bts570","article-title":"HiCNorm: removing biases in Hi-C data via Poisson regression","volume":"28","author":"Hu","year":"2012","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B19","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1038\/nmeth.2148","article-title":"Iterative correction of Hi-C data reveals hallmarks of chromosome organization","volume":"9","author":"Imakaev","year":"2012","journal-title":"Nat. Methods"},{"key":"2023062711301143200_btz048-B20","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.stem.2015.11.007","article-title":"3D chromosome regulatory landscape of human pluripotent cells","volume":"18","author":"Ji","year":"2016","journal-title":"Cell Stem Cell"},{"key":"2023062711301143200_btz048-B21","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1093\/imanum\/drs019","article-title":"A fast algorithm for matrix balancing","volume":"33","author":"Knight","year":"2012","journal-title":"IMA J. Numer. Anal"},{"key":"2023062711301143200_btz048-B22","doi-asserted-by":"crossref","first-page":"672","DOI":"10.1093\/bioinformatics\/btx623","article-title":"Diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data","volume":"34","author":"Lareau","year":"2018","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B23","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1126\/science.1181369","article-title":"Comprehensive mapping of long-range interactions reveals folding principles of the human genome","volume":"326","author":"Lieberman-Aiden","year":"2009","journal-title":"Science"},{"key":"2023062711301143200_btz048-B24","doi-asserted-by":"crossref","first-page":"165.","DOI":"10.1186\/1471-2105-6-165","article-title":"Identifying differential expression in multiple sage libraries: an overdispersed log-linear model approach","volume":"6","author":"Lu","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2023062711301143200_btz048-B25","doi-asserted-by":"crossref","first-page":"258.","DOI":"10.1186\/s12859-015-0683-0","article-title":"DiffHic: a bioconductor package to detect differential genomic interactions in Hi-C data","volume":"16","author":"Lun","year":"2015","journal-title":"BMC Bioinformatics"},{"key":"2023062711301143200_btz048-B26","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1515\/sagmb-2017-0010","article-title":"No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq data","volume":"16","author":"Lun","year":"2017","journal-title":"Stat. Appl. Genet. Mol. Biol"},{"key":"2023062711301143200_btz048-B27","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.gdata.2014.09.012","article-title":"Analysis of changes to mRNA levels and CTCF occupancy upon TFII-I knockdown","volume":"4","author":"Marques","year":"2015","journal-title":"Genom. Data"},{"key":"2023062711301143200_btz048-B28","doi-asserted-by":"crossref","first-page":"4288","DOI":"10.1093\/nar\/gks042","article-title":"Differential expression analysis of multifactor RNA-seq experiments with respect to biological variation","volume":"40","author":"McCarthy","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2023062711301143200_btz048-B29","doi-asserted-by":"crossref","first-page":"D658","DOI":"10.1093\/nar\/gkw983","article-title":"Cistrome data browser: a data portal for chip-seq and chromatin accessibility data in human and mouse","volume":"45","author":"Mei","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023062711301143200_btz048-B30","doi-asserted-by":"crossref","first-page":"390","DOI":"10.4161\/nucl.26513","article-title":"The statistical-mechanics of chromosome conformation capture","volume":"4","author":"O\u2019Sullivan","year":"2013","journal-title":"Nucleus"},{"key":"2023062711301143200_btz048-B31","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1093\/bioinformatics\/btu082","article-title":"HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization","volume":"30","author":"Paulsen","year":"2014","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B32","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1016\/j.cell.2009.06.001","article-title":"CTCF: master weaver of the genome","volume":"137","author":"Phillips","year":"2009","journal-title":"Cell"},{"key":"2023062711301143200_btz048-B33","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.molcel.2013.04.018","article-title":"Chromatin insulators: linking genome organization to cellular function","volume":"50","author":"Phillips-Cremins","year":"2013","journal-title":"Mol. Cell"},{"key":"2023062711301143200_btz048-B34","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1214\/16-AOAS920","article-title":"ROBUST hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression","volume":"10","author":"Phipson","year":"2016","journal-title":"Ann. Appl. Stat"},{"key":"2023062711301143200_btz048-B35","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.cell.2017.09.026","article-title":"Cohesin loss eliminates all loop domains","volume":"171","author":"Rao","year":"2017","journal-title":"Cell"},{"key":"2023062711301143200_btz048-B36","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1016\/j.cell.2014.11.021","article-title":"A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping","volume":"159","author":"Rao","year":"2014","journal-title":"Cell"},{"key":"2023062711301143200_btz048-B37","doi-asserted-by":"crossref","first-page":"9083","DOI":"10.1073\/pnas.1112570109","article-title":"Oncogene-mediated alterations in chromatin conformation","volume":"109","author":"Rickman","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023062711301143200_btz048-B38","doi-asserted-by":"crossref","first-page":"2881","DOI":"10.1093\/bioinformatics\/btm453","article-title":"Moderated statistical tests for assessing differences in tag abundance","volume":"23","author":"Robinson","year":"2007","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B39","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1093\/biostatistics\/kxm030","article-title":"Small-sample estimation of negative binomial dispersion, with applications to sage data","volume":"9","author":"Robinson","year":"2008","journal-title":"Biostatistics"},{"key":"2023062711301143200_btz048-B40","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"EdgeR: a bioconductor package for differential expression analysis of digital gene expression data","volume":"26","author":"Robinson","year":"2010","journal-title":"Bioinformatics"},{"key":"2023062711301143200_btz048-B41","doi-asserted-by":"crossref","first-page":"538.","DOI":"10.1186\/1471-2105-7-538","article-title":"Intensity-based hierarchical bayes method improves testing for differentially expressed genes in microarray experiments","volume":"7","author":"Sartor","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023062711301143200_btz048-B42","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.1039\/C4MB00142G","article-title":"Combining a wavelet change point and the bayes factor for analysing chromosomal interaction data","volume":"10","author":"Shavit","year":"2014","journal-title":"Mol. Biosyst"},{"key":"2023062711301143200_btz048-B43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2202\/1544-6115.1027","article-title":"Linear models and empirical bayes methods for assessing differential expression in microarray experiments","volume":"3","author":"Smyth","year":"2004","journal-title":"Stat. Appl. Genet. Mol. Biol"},{"key":"2023062711301143200_btz048-B44","doi-asserted-by":"crossref","first-page":"279.","DOI":"10.1186\/s12859-018-2288-x","article-title":"HiCcompare: an R-package for joint normalization and comparison of Hi-C datasets","volume":"19","author":"Stansfield","year":"2018","journal-title":"BMC Bioinformatics"},{"key":"2023062711301143200_btz048-B45","volume-title":"Adjustment During Army Life","author":"Stouffer","year":"1949"},{"key":"2023062711301143200_btz048-B46","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1101\/gr.201517.115","article-title":"Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations","volume":"26","author":"Taberlay","year":"2016","journal-title":"Genome Res"},{"key":"2023062711301143200_btz048-B47","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.gde.2016.03.008","article-title":"TAD disruption as oncogenic driver","volume":"36","author":"Valton","year":"2016","journal-title":"Curr. Opin. Genet. Dev"},{"key":"2023062711301143200_btz048-B48","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1016\/j.celrep.2015.02.004","article-title":"Comparative Hi-C reveals that CTCF underlies evolution of chromosomal domain architecture","volume":"10","author":"Vietri Rudan","year":"2015","journal-title":"Cell Rep"},{"key":"2023062711301143200_btz048-B50","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1038\/ng.947","article-title":"Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture","volume":"43","author":"Yaffe","year":"2011","journal-title":"Nat. Genet"},{"key":"2023062711301143200_btz048-B51","doi-asserted-by":"crossref","first-page":"42","DOI":"10.2202\/1544-6115.1701","article-title":"Fully moderated T-statistic for small sample size gene expression arrays","volume":"10","author":"Yu","year":"2011","journal-title":"Stat. Appl. Genet. Mol. Biol"},{"key":"2023062711301143200_btz048-B52","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1073\/pnas.1317788111","article-title":"Cohesin and CTCF differentially affect chromatin architecture and gene expression in human cells","volume":"111","author":"Zuin","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/17\/2916\/50719885\/bioinformatics_35_17_2916.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/17\/2916\/50719885\/bioinformatics_35_17_2916.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T11:32:53Z","timestamp":1687865573000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/35\/17\/2916\/5298730"}},"subtitle":[],"editor":[{"given":"Inanc","family":"Birol","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2019,1,22]]},"references-count":51,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2019,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btz048","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,9,1]]},"published":{"date-parts":[[2019,1,22]]}}}