{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T04:10:58Z","timestamp":1772165458769,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T00:00:00Z","timestamp":1604707200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T00:00:00Z","timestamp":1604707200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001475","name":"Nanyang Technological University","doi-asserted-by":"publisher","award":["Start-up grant"],"award-info":[{"award-number":["Start-up grant"]}],"id":[{"id":"10.13039\/501100001475","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001459","name":"Ministry of Education - Singapore","doi-asserted-by":"publisher","award":["Singapore Ministry of Education Academic Research Fund Tier 1"],"award-info":[{"award-number":["Singapore Ministry of Education Academic Research Fund Tier 1"]}],"id":[{"id":"10.13039\/501100001459","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>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hi-C and its variant techniques have been developed to capture the spatial organization of chromatin. Normalization of Hi-C contact map is essential for accurate modeling and interpretation of high-throughput chromatin conformation capture (3C) experiments. Hi-C correction tools were originally developed to normalize systematic biases of karyotypically normal cell lines. However, a vast majority of available Hi-C datasets are derived from cancer cell lines that carry multi-level DNA copy number variations (CNVs). CNV regions display over- or under-representation of interaction frequencies compared to CN-neutral regions. Therefore, it is necessary to remove CNV-driven bias from chromatin interaction data of cancer cell lines to generate a euploid-equivalent contact map.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We developed the HiCNAtra framework to compute high-resolution CNV profiles from Hi-C or 3C-seq data of cancer cell lines\u00a0and to correct chromatin contact maps from systematic biases including CNV-associated bias. First, we introduce a novel \u2018entire-fragment\u2019 counting method for better estimation of the read depth (RD) signal from Hi-C reads that recapitulates the whole-genome sequencing (WGS)-derived coverage signal. Second, HiCNAtra employs a multimodal-based hierarchical CNV calling approach, which outperformed OneD and HiNT tools, to accurately identify CNVs of cancer cell lines. Third, incorporating CNV information with other systematic biases, HiCNAtra simultaneously estimates the contribution of each bias and explicitly corrects the interaction matrix using Poisson regression. HiCNAtra normalization abolishes CNV-induced artifacts from the contact map generating a heatmap with homogeneous signal. When benchmarked against OneD, CAIC, and ICE methods using MCF7 cancer cell line, HiCNAtra-corrected heatmap achieves the least 1D signal variation without deforming the inherent chromatin interaction signal. Additionally, HiCNAtra-corrected contact frequencies have minimum correlations with each of the systematic bias sources compared to OneD\u2019s explicit method. Visual inspection of CNV profiles and contact maps of cancer cell lines reveals that HiCNAtra is the most robust Hi-C correction tool for ameliorating CNV-induced bias.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      HiCNAtra is a Hi-C-based computational tool that provides an analytical and visualization framework for DNA copy number profiling and chromatin\u00a0contact map correction of karyotypically abnormal cell lines. HiCNAtra is an open-source software implemented in MATLAB and is available at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/AISKhalil\/HiCNAtra\">https:\/\/github.com\/AISKhalil\/HiCNAtra<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-020-03832-8","type":"journal-article","created":{"date-parts":[[2020,11,7]],"date-time":"2020-11-07T07:02:44Z","timestamp":1604732564000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0391-0942","authenticated-orcid":false,"given":"Ahmed Ibrahim Samir","family":"Khalil","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siti Rawaidah Binte Mohammad","family":"Muzaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8818-6983","authenticated-orcid":false,"given":"Anupam","family":"Chattopadhyay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2109-4478","authenticated-orcid":false,"given":"Amartya","family":"Sanyal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,7]]},"reference":[{"issue":"1","key":"3832_CR1","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1101\/gad.179804.111","volume":"26","author":"E de Wit","year":"2012","unstructured":"de Wit E, de Laat W. A decade of 3C technologies: insights into nuclear organization. Genes Dev. 2012;26(1):11\u201324.","journal-title":"Genes Dev"},{"issue":"5558","key":"3832_CR2","doi-asserted-by":"publisher","first-page":"1306","DOI":"10.1126\/science.1067799","volume":"295","author":"J Dekker","year":"2002","unstructured":"Dekker J, et al. Capturing chromosome conformation. Science. 2002;295(5558):1306\u201311.","journal-title":"Science"},{"issue":"5950","key":"3832_CR3","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1126\/science.1181369","volume":"326","author":"E Lieberman-Aiden","year":"2009","unstructured":"Lieberman-Aiden E, et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 2009;326(5950):289\u201393.","journal-title":"Science"},{"issue":"3","key":"3832_CR4","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.cell.2012.01.010","volume":"148","author":"T Sexton","year":"2012","unstructured":"Sexton T, et al. Three-dimensional folding and functional organization principles of the Drosophila genome. Cell. 2012;148(3):458\u201372.","journal-title":"Cell"},{"issue":"7398","key":"3832_CR5","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1038\/nature11082","volume":"485","author":"JR Dixon","year":"2012","unstructured":"Dixon JR, et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature. 2012;485(7398):376\u201380.","journal-title":"Nature"},{"issue":"7398","key":"3832_CR6","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1038\/nature11049","volume":"485","author":"EP Nora","year":"2012","unstructured":"Nora EP, et al. Spatial partitioning of the regulatory landscape of the X-inactivation centre. Nature. 2012;485(7398):381\u20135.","journal-title":"Nature"},{"issue":"7559","key":"3832_CR7","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1038\/nature14450","volume":"523","author":"E Crane","year":"2015","unstructured":"Crane E, et al. Condensin-driven remodelling of X chromosome topology during dosage compensation. Nature. 2015;523(7559):240\u20134.","journal-title":"Nature"},{"issue":"5","key":"3832_CR8","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1016\/j.stem.2016.01.007","volume":"18","author":"PH Krijger","year":"2016","unstructured":"Krijger PH, et al. Cell-of-origin-specific 3D genome structure acquired during somatic cell reprogramming. Cell Stem Cell. 2016;18(5):597\u2013610.","journal-title":"Cell Stem Cell"},{"issue":"3","key":"3832_CR9","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1038\/nrg3123","volume":"13","author":"DJ Gordon","year":"2012","unstructured":"Gordon DJ, Resio B, Pellman D. Causes and consequences of aneuploidy in cancer. Nat Rev Genet. 2012;13(3):189\u2013203.","journal-title":"Nat Rev Genet"},{"issue":"4","key":"3832_CR10","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1016\/j.semcdb.2013.02.001","volume":"24","author":"LM Zasadil","year":"2013","unstructured":"Zasadil LM, Britigan EM, Weaver BA. 2n or not 2n: aneuploidy, polyploidy and chromosomal instability in primary and tumor cells. Semin Cell Dev Biol. 2013;24(4):370\u20139.","journal-title":"Semin Cell Dev Biol"},{"issue":"1","key":"3832_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1101\/cshperspect.a028373","volume":"7","author":"L Sansregret","year":"2017","unstructured":"Sansregret L, Swanton C. The role of aneuploidy in cancer evolution. Cold Spring Harb Perspect Med. 2017;7(1):1.","journal-title":"Cold Spring Harb Perspect Med"},{"issue":"4","key":"3832_CR12","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1002\/path.2724","volume":"221","author":"RP Brosens","year":"2010","unstructured":"Brosens RP, et al. Candidate driver genes in focal chromosomal aberrations of stage II colon cancer. J Pathol. 2010;221(4):411\u201324.","journal-title":"J Pathol"},{"issue":"11","key":"3832_CR13","doi-asserted-by":"publisher","first-page":"2698","DOI":"10.1016\/j.bbamcr.2014.08.001","volume":"1843","author":"O Krijgsman","year":"2014","unstructured":"Krijgsman O, et al. Focal chromosomal copy number aberrations in cancer-Needles in a genome haystack. Biochim Biophys Acta. 2014;1843(11):2698\u2013704.","journal-title":"Biochim Biophys Acta"},{"issue":"Spec No 1","key":"3832_CR14","doi-asserted-by":"publisher","first-page":"R57","DOI":"10.1093\/hmg\/ddl057","volume":"15","author":"L Feuk","year":"2006","unstructured":"Feuk L, et al. Structural variants: changing the landscape of chromosomes and design of disease studies. Hum Mol Genet. 2006;15(Spec No 1):R57-66.","journal-title":"Hum Mol Genet"},{"issue":"5","key":"3832_CR15","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1016\/j.cell.2015.04.004","volume":"161","author":"DG Lupianez","year":"2015","unstructured":"Lupianez DG, et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene-enhancer interactions. Cell. 2015;161(5):1012\u201325.","journal-title":"Cell"},{"issue":"1","key":"3832_CR16","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1038\/ng.3754","volume":"49","author":"R Beroukhim","year":"2016","unstructured":"Beroukhim R, Zhang X, Meyerson M. Copy number alterations unmasked as enhancer hijackers. Nat Genet. 2016;49(1):5\u20136.","journal-title":"Nat Genet"},{"issue":"6","key":"3832_CR17","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1101\/gr.201517.115","volume":"26","author":"PC Taberlay","year":"2016","unstructured":"Taberlay PC, et al. Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations. Genome Res. 2016;26(6):719\u201331.","journal-title":"Genome Res"},{"issue":"1","key":"3832_CR18","doi-asserted-by":"publisher","first-page":"1937","DOI":"10.1038\/s41467-017-01793-w","volume":"8","author":"P Wu","year":"2017","unstructured":"Wu P, et al. 3D genome of multiple myeloma reveals spatial genome disorganization associated with copy number variations. Nat Commun. 2017;8(1):1937.","journal-title":"Nat Commun"},{"issue":"7624","key":"3832_CR19","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1038\/nature19800","volume":"538","author":"M Franke","year":"2016","unstructured":"Franke M, et al. Formation of new chromatin domains determines pathogenicity of genomic duplications. Nature. 2016;538(7624):265\u20139.","journal-title":"Nature"},{"issue":"2","key":"3832_CR20","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1093\/bioinformatics\/btx664","volume":"34","author":"A Chakraborty","year":"2018","unstructured":"Chakraborty A, Ay F. Identification of copy number variations and translocations in cancer cells from Hi-C data. Bioinformatics. 2018;34(2):338\u201345.","journal-title":"Bioinformatics"},{"issue":"1","key":"3832_CR21","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1186\/s13059-020-01986-5","volume":"21","author":"S Wang","year":"2020","unstructured":"Wang S, et al. HiNT: a computational method for detecting copy number variations and translocations from Hi-C data. Genome Biol. 2020;21(1):73.","journal-title":"Genome Biol"},{"issue":"13","key":"3832_CR22","doi-asserted-by":"publisher","first-page":"6274","DOI":"10.1093\/nar\/gkw491","volume":"44","author":"R Xi","year":"2016","unstructured":"Xi R, et al. Copy number analysis of whole-genome data using BIC-seq2 and its application to detection of cancer susceptibility variants. Nucl Acids Res. 2016;44(13):6274\u201386.","journal-title":"Nucl Acids Res"},{"issue":"1","key":"3832_CR23","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1186\/s12859-020-3480-3","volume":"21","author":"AIS Khalil","year":"2020","unstructured":"Khalil AIS, et al. Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes. BMC Bioinform. 2020;21(1):147.","journal-title":"BMC Bioinform"},{"issue":"11","key":"3832_CR24","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1038\/ng.947","volume":"43","author":"E Yaffe","year":"2011","unstructured":"Yaffe E, Tanay A. Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture. Nat Genet. 2011;43(11):1059\u201365.","journal-title":"Nat Genet"},{"key":"3832_CR25","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.ymeth.2018.04.033","volume":"142","author":"R Golloshi","year":"2018","unstructured":"Golloshi R, Sanders JT, McCord RP. Iteratively improving Hi-C experiments one step at a time. Methods. 2018;142:47\u201358.","journal-title":"Methods"},{"issue":"8","key":"3832_CR26","doi-asserted-by":"publisher","first-page":"e49","DOI":"10.1093\/nar\/gky064","volume":"46","author":"E Vidal","year":"2018","unstructured":"Vidal E, et al. OneD: increasing reproducibility of Hi-C samples with abnormal karyotypes. Nucl Acids Res. 2018;46(8):e49.","journal-title":"Nucl Acids Res"},{"issue":"10","key":"3832_CR27","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1038\/nmeth.2148","volume":"9","author":"M Imakaev","year":"2012","unstructured":"Imakaev M, et al. Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat Methods. 2012;9(10):999\u20131003.","journal-title":"Nat Methods"},{"issue":"3","key":"3832_CR28","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1093\/imanum\/drs019","volume":"33","author":"PA Knight","year":"2013","unstructured":"Knight PA, Ruiz D. A fast algorithm for matrix balancing. IMA J Numer Anal. 2013;33(3):1029\u201347.","journal-title":"IMA J Numer Anal"},{"issue":"7","key":"3832_CR29","doi-asserted-by":"publisher","first-page":"1665","DOI":"10.1016\/j.cell.2014.11.021","volume":"159","author":"SS Rao","year":"2014","unstructured":"Rao SS, et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014;159(7):1665\u201380.","journal-title":"Cell"},{"issue":"1","key":"3832_CR30","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1186\/s12859-018-2256-5","volume":"19","author":"N Servant","year":"2018","unstructured":"Servant N, et al. Effective normalization for copy number variation in Hi-C data. BMC Bioinform. 2018;19(1):313.","journal-title":"BMC Bioinform"},{"issue":"6","key":"3832_CR31","doi-asserted-by":"publisher","first-page":"960","DOI":"10.1093\/bioinformatics\/btu747","volume":"31","author":"W Li","year":"2015","unstructured":"Li W, et al. Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data. Bioinformatics. 2015;31(6):960\u20132.","journal-title":"Bioinformatics"},{"issue":"23","key":"3832_CR32","doi-asserted-by":"publisher","first-page":"3131","DOI":"10.1093\/bioinformatics\/bts570","volume":"28","author":"M Hu","year":"2012","unstructured":"Hu M, et al. HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics. 2012;28(23):3131\u20133.","journal-title":"Bioinformatics"},{"issue":"24","key":"3832_CR33","doi-asserted-by":"publisher","first-page":"3695","DOI":"10.1093\/bioinformatics\/btw540","volume":"32","author":"HJ Wu","year":"2016","unstructured":"Wu HJ, Michor F. A computational strategy to adjust for copy number in tumor Hi-C data. Bioinformatics. 2016;32(24):3695\u2013701.","journal-title":"Bioinformatics"},{"issue":"3","key":"3832_CR34","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1093\/biostatistics\/kxq076","volume":"12","author":"F Picard","year":"2011","unstructured":"Picard F, et al. Joint segmentation, calling, and normalization of multiple CGH profiles. Biostatistics. 2011;12(3):413\u201328.","journal-title":"Biostatistics"},{"issue":"1","key":"3832_CR35","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1093\/bioinformatics\/btz540","volume":"36","author":"N Abdennur","year":"2020","unstructured":"Abdennur N, Mirny LA. Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics. 2020;36(1):311\u20136.","journal-title":"Bioinformatics"},{"issue":"7","key":"3832_CR36","doi-asserted-by":"publisher","first-page":"1050","DOI":"10.1128\/MCB.00652-15","volume":"36","author":"S Mishra","year":"2016","unstructured":"Mishra S, Whetstine JR. Different facets of copy number changes: permanent, transient, and adaptive. Mol Cell Biol. 2016;36(7):1050\u201363.","journal-title":"Mol Cell Biol"},{"issue":"2","key":"3832_CR37","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1038\/nrg1767","volume":"7","author":"L Feuk","year":"2006","unstructured":"Feuk L, Carson AR, Scherer SW. Structural variation in the human genome. Nat Rev Genet. 2006;7(2):85\u201397.","journal-title":"Nat Rev Genet"},{"issue":"3","key":"3832_CR38","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1016\/j.cell.2012.11.043","volume":"152","author":"YC Tang","year":"2013","unstructured":"Tang YC, Amon A. Gene copy-number alterations: a cost-benefit analysis. Cell. 2013;152(3):394\u2013405.","journal-title":"Cell"},{"issue":"4","key":"3832_CR39","first-page":"1809","volume":"43","author":"JS Horoszewicz","year":"1983","unstructured":"Horoszewicz JS, et al. LNCaP model of human prostatic carcinoma. Cancer Res. 1983;43(4):1809\u201318.","journal-title":"Cancer Res"},{"issue":"7718","key":"3832_CR40","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1038\/s41586-018-0409-3","volume":"560","author":"U Ben-David","year":"2018","unstructured":"Ben-David U, et al. Genetic and transcriptional evolution alters cancer cell line drug response. Nature. 2018;560(7718):325\u201330.","journal-title":"Nature"},{"key":"3832_CR41","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.ymeth.2014.10.031","volume":"72","author":"BR Lajoie","year":"2015","unstructured":"Lajoie BR, Dekker J, Kaplan N. The Hitchhiker\u2019s guide to Hi-C analysis: practical guidelines. Methods. 2015;72:65\u201375.","journal-title":"Methods"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03832-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03832-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03832-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T12:20:19Z","timestamp":1698322819000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03832-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,7]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["3832"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03832-8","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/798710","asserted-by":"object"}]},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,7]]},"assertion":[{"value":"14 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 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":"All the authors read and approved the final manuscript.","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":"506"}}