{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T14:12:58Z","timestamp":1776262378589,"version":"3.50.1"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"23","license":[{"start":{"date-parts":[[2017,6,5]],"date-time":"2017-06-05T00:00:00Z","timestamp":1496620800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HG006292"],"award-info":[{"award-number":["R01HG006292"]}],"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":["R01HL129132"],"award-info":[{"award-number":["R01HL129132"]}],"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":["U54DK107977"],"award-info":[{"award-number":["U54DK107977"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>High throughput chromatin conformation capture (3C) technologies, such as Hi-C and ChIA-PET, have the potential to elucidate the functional roles of non-coding variants. However, most of published genome-wide unbiased chromatin organization studies have used cultured cell lines, limiting their generalizability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We developed a web browser, HUGIn, to visualize Hi-C data generated from 21 human primary tissues and cell lines. HUGIn enables assessment of chromatin contacts both constitutive across and specific to tissue(s) and\/or cell line(s) at any genomic loci, including GWAS SNPs, eQTLs and cis-regulatory elements, facilitating the understanding of both GWAS and eQTL results and functional genomics data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>HUGIn is available at http:\/\/yunliweb.its.unc.edu\/HUGIn<\/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\/btx359","type":"journal-article","created":{"date-parts":[[2017,5,31]],"date-time":"2017-05-31T16:00:43Z","timestamp":1496246443000},"page":"3793-3795","source":"Crossref","is-referenced-by-count":67,"title":["HUGIn: Hi-C Unifying Genomic Interrogator"],"prefix":"10.1093","volume":"33","author":[{"given":"Joshua S","family":"Martin","sequence":"first","affiliation":[{"name":"Department of Genetics, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Nebraska, Lincoln, NE, USA"},{"name":"Quantitative Life Sciences Initiative, University of Nebraska, Lincoln, NE, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex P","family":"Reiner","sequence":"additional","affiliation":[{"name":"Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA"},{"name":"Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karen L","family":"Mohlke","sequence":"additional","affiliation":[{"name":"Department of Genetics, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Sullivan","sequence":"additional","affiliation":[{"name":"Department of Genetics, University of North Carolina, Chapel Hill, NC, USA"},{"name":"Department of Medical Epidemiology and Biostatistics, Karolinksa Institutet, Stockholm, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, UCSD Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Genetics, University of North Carolina, Chapel Hill, NC, USA"},{"name":"Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA"},{"name":"Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2017,6,5]]},"reference":[{"key":"2023020207003480100_btx359-B1","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1101\/gr.160374.113","article-title":"Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts","volume":"24","author":"Ay","year":"2014","journal-title":"Genome Res"},{"key":"2023020207003480100_btx359-B2","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.ajhg.2017.01.027","article-title":"Genetic regulation of adipose gene expression and cardio-metabolic traits","volume":"100","author":"Civelek","year":"2017","journal-title":"Am. 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