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Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions
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Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.
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“Mapping interactions between enhancers and promoters in disease-relevant cells improves the accuracy of the assignment (Grubert et al., 2015; McGeachie et al., 2016; Pomerantz et al., 2009), but this is not always feasible.”
From Insulated Neighborhoods: Structural and Functional Units of Mammalian Gene Control (2016) · cites this paper as Grubert et al., 2015
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Cites
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
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Bonev, B., & Cavalli, G. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.112 · Cited by 1,174
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Schoenfelder, S., & Fraser, P. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0128-0 · Cited by 1,102
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“We have analyzed our ChIA-PET data using two analytical approaches: one that estimates the background contact frequency based on the genomic proximity bias (Mango pipeline) adapted from previous reports (24, 30, 40), and an analytical approach that estimates the background contact frequency based on the ligation frequ…”
BackgroundMethodComprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965
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Long, H. K., Prescott, S. L., & Wysocka, J. (2016) · Cell · doi:10.1016/j.cell.2016.09.018 · Cited by 945
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Chen, L., Ge, B., Casale, F. P., Vasquez, L., Kwan, T., Garrido-Martín, D., Watt, S., Yan, Y., Kundu, K., Ecker, S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.026 · Cited by 679
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Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science · doi:10.1126/science.aad9417 · Cited by 660
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Sequential regulatory activity prediction across chromosomes with convolutional neural networks
Kelley, D. R., Reshef, Y. A., Bileschi, M., Belanger, D., McLean, C. Y., & Snoek, J. (2018) · Genome Research · doi:10.1101/gr.227819.117 · Cited by 537
Gusev, A., Mancuso, N., Won, H., Kousi, M., Finucane, H. K., Reshef, Y., Song, L., Safi, A., Schizophrenia Working Group of the Psychiatric Genomics Consortium, McCarroll, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0092-1 · Cited by 491
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Bonder, M. J., Luijk, R., Zhernakova, D. V., Moed, M., Deelen, P., Vermaat, M., van Iterson, M., van Dijk, F., van Galen, M., Bot, J. J., et al. (2016) · Nature Genetics · doi:10.1038/ng.3721 · Cited by 462
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Deplancke, B., Alpern, D., & Gardeux, V. (2016) · Cell · doi:10.1016/j.cell.2016.07.012 · Cited by 390
Insulated Neighborhoods: Structural and Functional Units of Mammalian Gene Control
Hnisz, D., Day, D. S., & Young, R. A. (2016) · Cell · doi:10.1016/j.cell.2016.10.024 · Cited by 420
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Denker, A., & de Laat, W. L. (2016) · Genes & Development · doi:10.1101/gad.281964.116 · Cited by 357
HIPSCI Consortium, Alasoo, K., Rodrigues, J., Mukhopadhyay, S., Knights, A. J., Mann, A. L., Kundu, K., Hale, C., Dougan, G., & Gaffney, D. J. (2018) · Nature Genetics · doi:10.1038/s41588-018-0046-7 · Cited by 338
Regulation of disease-associated gene expression in the 3D genome
Krijger, P. H. L., & de Laat, W. L. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.138 · Cited by 332
Histone Acetylome-wide Association Study of Autism Spectrum Disorder
Sun, W., Poschmann, J., Cruz-Herrera del Rosario, R., Parikshak, N. N., Hajan, H. S., Kumar, V., Ramasamy, R., Belgard, T. G., Elanggovan, B., Wong, C. C. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.031 · Cited by 306
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Weidemüller, P., Kholmatov, M. M., Petsalaki, E., & Zaugg, J. B. (2021) · PROTEOMICS · doi:10.1002/pmic.202000034 · Cited by 295
Methods for ChIP-seq analysis: A practical workflow and advanced applications
Nakato, R., & Sakata, T. (2021) · Methods · doi:10.1016/j.ymeth.2020.03.005 · Cited by 267
The impact of rare variation on gene expression across tissues
Li, X., Kim, Y., Tsang, E. K., Davis, J. R., Damani, F. N., Chiang, C., Hess, G. T., Zappala, Z., Strober, B. J., Scott, A. J., et al. (2017) · Nature · doi:10.1038/nature24267 · Cited by 253
Chromatin accessibility dynamics in a model of human forebrain development
Trevino, A. E., Sinnott-Armstrong, N., Andersen, J., Yoon, S.-J., Huber, N., Pritchard, J. K., Chang, H. Y., Greenleaf, W. J., & Pașca, S. P. (2020) · Science · doi:10.1126/science.aay1645 · Cited by 251
Self-citationNeuron-specific signatures in the chromosomal connectome associated with schizophrenia risk
Rajarajan, P., Borrman, T., Liao, W., Schrode, N., Flaherty, E., Casiño, C., Powell, S., Yashaswini, C., LaMarca, E. A., Kassim, B., et al. (2018) · Science · doi:10.1126/science.aat4311 · Cited by 219
Chromatin three-dimensional interactions mediate genetic effects on gene expression
Delaneau, O., Zazhytska, M., Borel, C., Giannuzzi, G., Rey, G., Howald, C., Kumar, S., Ongen, H., Popadin, K. Y., Marbach, D., et al. (2019) · Science · doi:10.1126/science.aat8266 · Cited by 212
Link, V. M., Duttke, S. H., Chun, H. B., Holtman, I. R., Westin, E., Hoeksema, M. A., Abe, Y., Skola, D., Romanoski, C. E., Tao, J., et al. (2018) · Cell · doi:10.1016/j.cell.2018.04.018 · Cited by 182
McCord, R. P., Kaplan, N., & Giorgetti, L. (2020) · Molecular Cell · doi:10.1016/j.molcel.2019.12.021 · Cited by 220
Landscape of cohesin-mediated chromatin loops in the human genome
Grubert, F., Srivas, R., Spacek, D. V., Kasowski, M. M., Ruiz-Velasco, M., Sinnott-Armstrong, N., Greenside, P., Narasimha, A. M., Liu, Q., Geller, B. S., et al. (2020) · Nature · doi:10.1038/s41586-020-2151-x · Cited by 203
Takata, A., Matsumoto, N., & Kato, T. (2017) · Nature Communications · doi:10.1038/ncomms14519 · Cited by 192
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Zhang, Z. S., Luo, K., Zou, Z., Qiu, M., Tian, J., Sieh, L., Shi, H., Zou, Y., Wang, G., Morrison, J., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0644-z · Cited by 192
Hormozdiari, F., Gazal, S., van de Geijn, B., Finucane, H. K., Ju, C. J. ‐., Loh, P., Schoech, A. P., Reshef, Y., Liu, X., O’Connor, L. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0148-2 · Cited by 176
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Girdhar, K., Hoffman, G. E., Jiang, Y., Brown, L., Kundakovic, M., Hauberg, M. E., Francoeur, N. J., Wang, Y.-C., Shah, H., Kavanagh, D. H., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0187-0 · Cited by 139
Greenwald, W. W. Y., Li, H., Benaglio, P., Jakubosky, D. A., Matsui, H., Schmitt, A. D., Selvaraj, S., D’Antonio, M., D’Antonio‐Chronowska, A., Smith, E. N., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08940-5 · Cited by 144
Zheng, Z., Huang, D., Wang, J., Zhao, K., Zhou, Y., Guo, Z., Zhai, S., Xu, H., Cui, H. S., Yao, H., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz888 · Cited by 142
Lam, M., Trampush, J. W., Yu, J., Knowles, E., Davies, G., Liewald, D. C. M., Starr, J. M., Djurovic, S., Melle, I., Sundet, K. S., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.11.028 · Cited by 123
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Forrest, M. P., Zhang, H., Moy, W., McGowan, H., Leites, C., Dionisio, L. E., Xu, Z., Shi, J., Sanders, A. R., Greenleaf, W. J., et al. (2017) · Cell stem cell · doi:10.1016/j.stem.2017.07.008 · Cited by 120
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Madsen, J. G. S., Madsen, M. S., Rauch, A., Traynor, S., Hauwaert, E. L. V., Haakonsson, A. K., Javierre, B. M., Hyldahl, M., Fraser, P., & Mandrup, S. (2020) · Nature Genetics · doi:10.1038/s41588-020-0709-z · Cited by 97
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Iglesias, A. I., Mishra, A., Vitart, V., Bykhovskaya, Y., Höhn, R., Springelkamp, H., Cuéllar-Partida, G., Gharahkhani, P., Bailey, J. N. C., Willoughby, C. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03646-6 · Cited by 95
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Cheung, W., Shao, X., Morin, A., Siroux, V., Kwan, T., Ge, B., Aïssi, D., Chen, L., Vasquez, L. J., Allum, F., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1173-7 · Cited by 94
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Ecker, S., Pancaldi, V., Valencia, A., Beck, S., & Paul, D. S. (2017) · BioEssays · doi:10.1002/bies.201700148 · Cited by 93
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Gorkin, D. U., Qiu, Y., Hu, M., Fletez‐Brant, K., Liu, T., Schmitt, A. D., Noor, A., Chiou, J., Gaulton, K. J., Sebat, J. L., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1855-4 · Cited by 82
Current challenges in understanding the role of enhancers in disease
Zaugg, J. B., Sahlén, P., Andersson, R., Alberich-Jordà, M., de Laat, W. L., Deplancke, B., Ferrer, J. P., Mandrup, S., Natoli, G., Plewczyński, D., et al. (2022) · Nature Structural & Molecular Biology · doi:10.1038/s41594-022-00896-3 · Cited by 86
Transcriptional enhancers and their communication with gene promoters
Ray-Jones, H., & Spivakov, M. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-03903-w · Cited by 81
Reyes‐Palomares, A., Gu, M., Grubert, F., Berest, I., Sa, S., Kasowski, M. M., Arnold, C., Mao, S., Srivas, R., Miao, S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15463-x · Cited by 81
Understanding the 3D genome: Emerging impacts on human disease
Krumm, A., & Duan, Z. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.004 · Cited by 76
Heinig, M., Adriaens, M. E., Schäfer, S., van Deutekom, H. W. M., Lodder, E. M., Ware, J. S., Schneider-Lunitz, V., Felkin, L. E., Creemers, E. E., Meder, B., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1286-z · Cited by 74
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Orlando, G., Law, P., Cornish, A. J., Dobbins, S. E., Chubb, D., Broderick, P., Litchfield, K., Hariri, F., Pastinen, T., Osborne, C. S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0211-z · Cited by 74
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Richardson, T. G., Zheng, J., Smith, G. D., Timpson, N. J., Gaunt, T. R., Relton, C. L., & Hemani, G. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.09.003 · Cited by 71
Intergenic disease-associated regions are abundant in novel transcripts
Bartoniček, N., Clark, M. B., Quek, X. C., Torpy, J., Pritchard, A. L., Mååg, J. L. V., Gloss, B., Crawford, J., Taft, R. J., Hayward, N. K., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1363-3 · Cited by 72
Gene regulation in the 3D genome
Li, Y., Hu, M., & Shen, Y. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy164 · Cited by 71
Fine-mapping cis-regulatory variants in diverse human populations
Tehranchi, A. K., Hie, B., Dacre, M., Kaplow, I. M., Pettie, K. P., Combs, P. A., & Fraser, H. B. (2019) · eLife · doi:10.7554/elife.39595 · Cited by 69
Baca, S. C., Singler, C., Zacharia, S., Seo, J.-H., Morova, T., Hach, F., Ding, Y., Schwarz, T., Huang, C.-C. F., Anderson, J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01168-y · Cited by 61
MAnorm2 for quantitatively comparing groups of ChIP-seq samplesPreprint
Tu, S., Li, M., Tan, F., Chen, H., Xu, J., Waxman, D. J., Zhang, Y., & Shao, Z. (2020) · Genome Research · doi:10.1101/gr.262675.120 · Cited by 64
Gusev, A., Mancuso, N., Finucane, H. K., Reshef, Y., Song, L., Safi, A., Oh, E. C. T., McCarroll, S. A., Neale, B. M., Ophoff, R. A., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/067355 · Cited by 66
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Ye, Y., Zhang, Z., Liu, Y., Diao, L., & Han, L. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.01.009 · Cited by 68
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Floris, M., Olla, S., Schlessinger, D., & Cucca, F. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.04.004 · Cited by 67
Cheung, W., Shao, X., Morin, A., Siroux, V., Kwan, T., Ge, B., Aïssi, D., Chen, L., Vasquez, L. J., Allum, F., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1702-7 · Cited by 65
Hoffman, G. E., Bendl, J. M., Girdhar, K., Schadt, E. E., & Roussos, P. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz808 · Cited by 63
Osman, A. A., Arslan, E., Bartels, M. D., Michikawa, C., Lindemann, A., Tomczak, K. J., Yu, W., Sandulache, V. C., Ma, W., Shen, L., et al. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-2747 · Cited by 63
Xin, B., & Rohs, R. (2018) · Genome Research · doi:10.1101/gr.220079.116 · Cited by 63
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Akiyama, M. (2020) · Journal of Human Genetics · doi:10.1038/s10038-020-00842-5 · Cited by 63
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Ignatiadis, N., & Huber, W. K. (2021) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12411 · Cited by 75
Allen, M., Wang, X., Serie, D., Strickland, S. L., Burgess, J. D., Koga, S., Younkin, C. S., Nguyen, T., Malphrus, K. G., Lincoln, S., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1900-5 · Cited by 54
Watt, S., Vasquez, L., Walter, K., Mann, A. L., Kundu, K., Chen, L., Sims, Y., Ecker, S., Burden, F., Farrow, S., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22548-8 · Cited by 63
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Song, Y., Xu, X., Wang, W., Tian, T., Zhu, Z., & Yang, C. J. (2019) · The Analyst · doi:10.1039/c8an01852a · Cited by 56
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Pierce, B. L., Kraft, P., & Zhang, C. (2018) · Current Epidemiology Reports · doi:10.1007/s40471-018-0144-1 · Cited by 55
Cavalli, M., Pan, G., Nord, H., Wallerman, O., Arzt, E. W., Berggren, O., Elvers, I., Eloranta, M., Rönnblom, L., Lindblad‐Toh, K., et al. (2016) · Human Genetics · doi:10.1007/s00439-016-1654-x · Cited by 52
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Unravelling the complex genetics of common kidney diseases: from variants to mechanisms
Sullivan, K. M., & Suszták, K. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0298-1 · Cited by 52
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Hoeksema, M. A., Shen, Z., Holtman, I. R., Zheng, A., Spann, N. J., Cobo, I., Gymrek, M., & Glass, C. K. (2021) · Science Advances · doi:10.1126/sciadv.abf9808 · Cited by 51
Phelps, S. M., Okhovat, M., & Berrío, A. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00537 · Cited by 52
Metadata
- Authors
- Grubert, F., Zaugg, J. B., Kasowski, M., Ursu, O., Spacek, D. V., Martin, A. R., Greenside, P., Srivas, R., Phanstiel, D. H., Pekowska, A., Heidari, N., Euskirchen, G., Huber, W., Pritchard, J. K., Bustamante, C. D., Steinmetz, L. M., Kundaje, A., & Snyder, M.
- Affiliations
- Stanford Medicine (US)
- European Molecular Biology Laboratory (DE)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Snyder, Michael
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 162
- Issue
- 5
- Pages
- 1051-1065
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4556133
- OpenAlex
- W2112673809
- Cited by
- 319
- References
- 56
- Citations by year
- 2026: 12 · 2025: 13 · 2024: 18 · 2023: 21 · 2022: 25 · 2021: 23 · 2020: 37 · 2019: 39 · 2018: 48 · 2017: 39 · 2016: 36 · 2015: 8
- FWCI
- 18.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Howard Hughes Medical Institute
- National Heart, Lung, and Blood Institute (R01HL122887, U01HL107393)
- National Human Genome Research Institute (U41HG007000, U54HG006996, R00HG008662, K99HG008662, U41-HG007000-02S1, P50HG007735, U01HG007919, P01HG000205, T32HG000044)
- National Institute of General Medical Sciences (T32GM007790, T32GM007205)
- National Institute of Environmental Health Sciences (R01ES025009)
- U.S. National Library of Medicine (LM 07033, T15LM007033)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- histone modifications, chromatin state, long-range chromatin interactions, topologically associating domains, non-coding variants, gene expression regulation, lymphoblastoid cell lines, Hi-C, ChIA-PET
- MeSH terms
- Cell Line, Chromatin, Chromosomes, Human, Female, Histones, Humans, Lymphocytes, Male, Cohort Studies, Human Genome Project, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Gene Regulatory Networks, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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