CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works

A Simplex Method for Function Minimization

Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905 · see citing works

An integrated encyclopedia of DNA elements in the human genome

The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works

Differential expression analysis for sequence count data

Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581 · see citing works

Simple Combinations of Lineage-Determining Transcription Factors Prime cis-Regulatory Elements Required for Macrophage and B Cell Identities

Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works

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 · see citing works

Systematic Localization of Common Disease-Associated Variation in Regulatory DNA

Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716 · see citing works

Orchestrating high-throughput genomic analysis with Bioconductor

Huber, W. K., Carey, V. J., Gentleman, R. C., Anders, S., Carlson, M. R. J., Carvalho, B. S., Bravo, H. C., Davis, S. R., Gatto, L., Girke, T., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3252 · Cited by 3,499 · see citing works

ChromHMM: automating chromatin-state discovery and characterization

Ernst, J., & Kellis, M. (2012) · Nature Methods · doi:10.1038/nmeth.1906 · Cited by 2,489 · see citing works

Dynamic regulation of genome-wide pre-mRNA splicing and stress tolerance by the Sm-like protein LSm5 in Arabidopsis

Cui, P., Zhang, S., Ding, F. H., Ali, S., & Xiong, L. (2014) · Genome biology · doi:10.1186/gb-2014-15-1-r1 · Cited by 2,282 · see citing works

A comparative encyclopedia of DNA elements in the mouse genome

Yue, F., Cheng, Y., Breschi, A., Vierstra, J., Wu, W., Ryba, T., Sandstrom, R., Ma, Z., Davis, C., Pope, B. D., et al. (2014) · Nature · doi:10.1038/nature13992 · Cited by 1,781 · see citing works

The long-range interaction landscape of gene promoters

Sanyal, A., Lajoie, B. R., Jain, G., & Dekker, J. (2012) · Nature · doi:10.1038/nature11279 · Cited by 1,489 · see citing works

Iterative correction of Hi-C data reveals hallmarks of chromosome organization

Imakaev, M., Fudenberg, G., McCord, R. P., Naumova, N., Goloborodko, A., Lajoie, B. R., Dekker, J., & Mirny, L. A. (2012) · Nature Methods · doi:10.1038/nmeth.2148 · Cited by 1,423 · see citing works

Exploring the three-dimensional organization of genomes: Interpreting chromatin interaction data

Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3454 · Cited by 1,068 · see citing works

CTCF: an architectural protein bridging genome topology and function

Ong, C., & Corces, V. G. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3663 · Cited by 1,044 · see citing works

Measuring reproducibility of high-throughput experiments

Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2011) · The Annals of Applied Statistics · doi:10.1214/11-aoas466 · Cited by 1,008 · see citing works

Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C

Mifsud, B., Tavares-Cadete, F., Young, A. N., Sugar, R., Schoenfelder, S., Ferreira, L., Wingett, S. W., Andrews, S., Grey, W., Ewels, P. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3286 · Cited by 990 · see citing works

Measuring reproducibility of high-throughput experiments

Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2010) · UC Berkeley · Cited by 915 · see citing works

HiCUP: pipeline for mapping and processing Hi-C data

Wingett, S., Ewels, P., Furlan-Magaril, M., Nagano, T., Schoenfelder, S., Fraser, P., & Andrews, S. (2015) · F1000Research · doi:10.12688/f1000research.7334.1 · Cited by 724 · see citing works

ArrayExpress update—simplifying data submissions

Kolesnikov, N. N., Hastings, E., Keays, M., Melnichuk, O., Tang, A., Williams, E. M., Dylag, M., Kurbatova, N., Brandizi, M., Burdett, T., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1057 · Cited by 700 · see citing works

Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture

Yaffe, E., & Tanay, A. (2011) · Nature Genetics · doi:10.1038/ng.947 · Cited by 645 · see citing works

Data-driven hypothesis weighting increases detection power in genome-scale multiple testing

Ignatiadis, N., Klaus, B., Zaugg, J. B., & Huber, W. K. (2016) · Nature Methods · doi:10.1038/nmeth.3885 · Cited by 622 · see citing works

Statistical confidence estimation for Hi-C data reveals regulatory chromatin contactsPreprint

Ay, F., Bailey, T. L., & Noble, W. S. (2014) · Genome Research · doi:10.1101/gr.160374.113 · Cited by 479 · see citing works

The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements

Schoenfelder, S., Furlan-Magaril, M., Mifsud, B., Tavares-Cadete, F., Sugar, R., Javierre, B.-M., Nagano, T., Katsman, Y., Sakthidevi, M., Wingett, S. W., et al. (2015) · Genome Research · doi:10.1101/gr.185272.114 · Cited by 460 · see citing works

Multiple Testing Procedures with Applications to Genomics

Dudoit, S., & van der Laan, M. J. (2007) · Springer series in statistics · doi:10.1007/978-0-387-49317-6 · Cited by 453 · see citing works

Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome

Schoenfelder, S., Sugar, R., Dimond, A., Javierre, B.-M., Armstrong, H., Mifsud, B., Dimitrova, E., Matheson, L., Tavares-Cadete, F., Furlan-Magaril, M., et al. (2015) · Nature Genetics · doi:10.1038/ng.3393 · Cited by 398 · see citing works

Robust 4C-seq data analysis to screen for regulatory DNA interactions

van de Werken, H. J. G., Landan, G., Holwerda, S. J. B., Hoichman, M., Klous, P., Chachik, R., Splinter, E., Valdes‐Quezada, C., Öz, Y., Bouwman, B. A. M., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2173 · Cited by 376 · see citing works

Cell cycle–regulated phosphorylation of p220 NPAT by cyclin E/Cdk2 in Cajal bodies promotes histone gene transcriptionPreprint

Ma, T., Tine, B. A. V., Yue, W., Garrett, M. D., Nelson, D. M., Adams, P. D., Wang, J., Qin, J., Chow, L. T., & Harper, J. W. (2000) · Genes & Development · doi:10.1101/gad.829500 · Cited by 373 · see citing works

The RNA-binding protein hnRNPLL induces a T cell alternative splicing program delineated by differential intron retention in polyadenylated RNA

Cho, V., Mei, Y., Sanny, A., Chan, S., Enders, A., Bertram, E. M., Tan, A. H., Goodnow, C. C., & Andrews, T. D. (2014) · Genome biology · doi:10.1186/gb-2014-15-1-r26 · Cited by 339 · see citing works

False discovery control with p-value weighting

Genovese, C. R., Roeder, K., & Wasserman, L. (2006) · Biometrika · doi:10.1093/biomet/93.3.509 · Cited by 337 · see citing works

Chromatin Position Effects Assayed by Thousands of Reporters Integrated in Parallel

Akhtar, W., de Jong, J., Pindyurin, A. V., Pagie, L., Meuleman, W. R. A., de Ridder, J., Berns, A. J. M., Wessels, L. F. A., van Lohuizen, M., & van Steensel, B. (2013) · Cell · doi:10.1016/j.cell.2013.07.018 · Cited by 318 · see citing works

Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-CPreprint

Dryden, N. H., Broome, L. R., Dudbridge, F., Johnson, N., Orr, N., Schoenfelder, S., Nagano, T., Andrews, S., Wingett, S., Kozarewa, I., et al. (2014) · Genome Research · doi:10.1101/gr.175034.114 · Cited by 254 · see citing works

HiCNorm: removing biases in Hi-C data via Poisson regression

Hu, M., Deng, K., Selvaraj, S., Qin, Z., Ren, B., & Liu, J. S. (2012) · Bioinform. · doi:10.1093/bioinformatics/bts570 · Cited by 250 · see citing works

Genomics tools for unraveling chromosome architecture

van Steensel, B., & Dekker, J. (2010) · Nature Biotechnology · doi:10.1038/nbt.1680 · Cited by 216 · see citing works

Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci

Jäger, R., Migliorini, G., Henrion, M., Kandaswamy, R., Speedy, H. E., Heindl, A., Whiffin, N., Carnicer, M. J., Broome, L. R., Dryden, N. H., et al. (2015) · Nature Communications · doi:10.1038/ncomms7178 · Cited by 210 · see citing works

Exploring long-range genome interactions using the WashU Epigenome Browser

Zhou, X., Lowdon, R. F., Li, D., Lawson, H. A., Madden, P. A. F., Costello, J., & Wang, T. (2013) · Nature Methods · doi:10.1038/nmeth.2440 · Cited by 209 · see citing works

Diffusion-Driven Looping Provides a Consistent Framework for Chromatin Organization

Bohn, M., & Heermann, D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012218 · Cited by 168 · see citing works

Cajal bodies are linked to genome conformation

Wang, Q., Sawyer, I. A., Sung, M.-H., Sturgill, D., Shevtsov, S. P., Pegoraro, G., Hakim, O., Baek, S., Hager, G. L., & Dundr, M. (2016) · Nature Communications · doi:10.1038/ncomms10966 · Cited by 164 · see citing works

Stratified false discovery control for large‐scale hypothesis testing with application to genome‐wide association studies

Sun, L., Craiu, R. V., Paterson, A. D., & Bull, S. B. (2006) · Genetic Epidemiology · doi:10.1002/gepi.20164 · Cited by 149 · see citing works

Genome-wide mapping of promoter-anchored interactions with close to single-enhancer resolution

Sahlén, P., Abdullayev, I., Ramsköld, D., Matskova, L. V., Rilakovic, N., Lötstedt, B., Albert, T. J., Lundeberg, J., & Sandberg, R. (2015) · Genome biology · doi:10.1186/s13059-015-0727-9 · Cited by 131 · see citing works

Looping Probabilities in Model Interphase Chromosomes

Rosa, A., Becker, N. B., & Everaers, R. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2010.01.054 · Cited by 124 · see citing works

Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci

Trynka, G., Westra, H.-J., Slowikowski, K., Hu, X., Xu, H., Stranger, B. E., Klein, R. J., Han, B., & Raychaudhuri, S. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.05.016 · Cited by 114 · see citing works

r3Cseq: an R/Bioconductor package for the discovery of long-range genomic interactions from chromosome conformation capture and next-generation sequencing data

Thongjuea, S., Stadhouders, R., Grosveld, F. G., Soler, É., & Lenhard, B. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt373 · Cited by 113 · see citing works

Genome-Wide Significance Levels and Weighted Hypothesis Testing

Roeder, K., & Wasserman, L. (2009) · Statistical Science · doi:10.1214/09-sts289 · Cited by 110 · see citing works

Genome-wide significance levels and weighted hypothesis testingPreprint

Roeder, K., & Wasserman, L. (2009) · Cited by 96 · see citing works

FourCSeq: analysis of 4C sequencing data

Klein, F. A., Pakozdi, T., Anders, S., Ghavi-Helm, Y., Furlong, E. E. M., & Huber, W. K. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv335 · Cited by 94 · see citing works

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data

Mifsud, B., Martincorena, I., Darbo, É., Sugar, R., Schoenfelder, S., Fraser, P., & Luscombe, N. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0174744 · Cited by 89 · see citing works

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments

Raviram, R., Rocha, P. P., Müller, C. L., Miraldi, E. R., Badri, S., Fu, Y., Swanzey, E., Proudhon, C., Snetkova, V., Bonneau, R., et al. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004780 · Cited by 89 · see citing works

The role of transcription factories in large-scale structure and dynamics of interphase chromatin

Sexton, T., Umlauf, D., Kurukuti, S., & Fraser, P. (2007) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2007.08.008 · Cited by 70 · see citing works

Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

Li, L., Kabesch, M., Bouzigon, E., Démenais, F., Farrall, M., Moffatt, M. F., Lin, X., & Liang, L. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00103 · Cited by 59 · see citing works

A hidden Markov random field-based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data

Xu, Z. Q., Zhang, G., Jin, F., Chen, M., Furey, T. S., Sullivan, P. F., Qin, Z. S., Hu, M., & Li, Y. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv650 · Cited by 48 · see citing works

Weighted multiple testing procedures for genomic studies

Gui, J., Tosteson, T. D., & Borsuk, M. E. (2012) · BioData Mining · doi:10.1186/1756-0381-5-4 · Cited by 21 · see citing works

Improving Power of Genome-Wide Association Studies with Weighted False Discovery Rate Control and Prioritized Subset Analysis

Lin, W., & Lee, W. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033716 · Cited by 13 · see citing works

sdef: an R package to synthesize lists of significant features in related experiments

Blangiardo, M., Cassese, A., & Richardson, S. T. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-270 · Cited by 10 · see citing works

GOTHiC, a simple probabilistic model to resolve complex biases and to identify real interactions in Hi-C dataPreprint

Mifsud, B., Martincorena, I., Darbo, É., Sugar, R., Schoenfelder, S., Fraser, P., & Luscombe, N. M. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/023317 · Cited by 10 · see citing works

A powerful FDR control procedure for multiple hypotheses

Zhao, H., & Fung, W. K. (2016) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2015.12.013 · Cited by 10 · see citing works

Discovering collectively informative descriptors from high-throughput experiments

Jeffries, C. D., Ward, W. O., Perkins, D. O., & Wright, F. A. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-431 · Cited by 5 · see citing works

Integrating experimental and computational approaches for the proteogenomic characterizations of microbial communities

Hettich, R. L., Russell, A. L., VerBerkmoes, N. C., Shah, M. B., Fraser, C. M., & Jansson, J. K. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-s4-o6 · Cited by 2 · see citing works

Analysis of Promoter Capture Hi-C data for GM12878 and mouse ES cells using the CHiCAGO pipelinePreprint

Cairns, J., Pritchett, P. F., Wingett, S., & Spivakov, M. (2016) · Cited by 1 · see citing works

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

Fishilevich, S., Nudel, R., Rappaport, N., Hadar, R., Plaschkes, I., Stein, T. I., Rosen, N., Kohn, A., Twik, M., Safran, M., et al. (2017) · Database · doi:10.1093/database/bax028 · Cited by 1,219 · see citing works

Long-range enhancer–promoter contacts in gene expression control

Schoenfelder, S., & Fraser, P. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0128-0 · Cited by 1,102 · see citing works

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.037 · Cited by 1,046 · see citing works

Cicero predicts cis-regulatory DNA interactions from single-cell chromatin accessibility data

Pliner, H. A., Packer, J. S., McFaline-Figueroa, J. L., Cusanovich, D. A., Daza, R. M., Aghamirzaie, D., Srivatsan, S., Qiu, X., Jackson, D., Minkina, A., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.06.044 · Cited by 789 · see citing works

HiCUP: pipeline for mapping and processing Hi-C data

Wingett, S., Ewels, P., Furlan-Magaril, M., Nagano, T., Schoenfelder, S., Fraser, P., & Andrews, S. (2015) · F1000Research · doi:10.12688/f1000research.7334.1 · Cited by 724 · see citing works

Methods for mapping 3D chromosome architecture

Kempfer, R., & Pombo, A. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0195-2 · Cited by 502 · see citing works

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

Weeks, E. M., Ulirsch, J. C., Cheng, N., Trippe, B. L., Fine, R. S., Miao, J., Patwardhan, T. A., Kanai, M., Nasser, J., Fulco, C. P., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01443-6 · Cited by 330 · see citing works

The second decade of 3C technologies: detailed insights into nuclear organizationPreprint

Denker, A., & de Laat, W. L. (2016) · Genes & Development · doi:10.1101/gad.281964.116 · Cited by 346 · see citing works

Highly rearranged chromosomes reveal uncoupling between genome topology and gene expression

Ghavi-Helm, Y., Jankowski, A., Meiers, S., Viales, R. R., Korbel, J. O., & Furlong, E. E. M. (2019) · Nature Genetics · doi:10.1038/s41588-019-0462-3 · Cited by 354 · see citing works

Genome-wide mapping and analysis of chromosome architecture

Schmitt, A. D., Hu, M., & Ren, B. (2016) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2016.104 · Cited by 344 · see citing works

Lineage-specific dynamic and pre-established enhancer-promoter contacts cooperate in terminal differentiation

Rubin, A. J., Barajas, B. C., Furlan-Magaril, M., Lopez-Pajares, V., Mumbach, M. R., Howard, I., Kim, D. S., Boxer, L. D., Cairns, J., Spivakov, M., et al. (2017) · Nature Genetics · doi:10.1038/ng.3935 · Cited by 293 · see citing works

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes

Miguel-Escalada, I., Bonàs‐Guarch, S., Cebola, I., Ponsa-Cobas, J., Mendieta-Esteban, J., Atla, G., Javierre, B. M., Rolando, D., Farabella, I., Morgan, C. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0457-0 · Cited by 259 · see citing works

Association analyses identify 31 new risk loci for colorectal cancer susceptibility

Law, P., Timofeeva, M. N., Fernández–Rozadilla, C., Broderick, P., Studd, J. B., Fernandez-Tajes, J. J., Farrington, S. M., Svinti, V., Palles, C., Orlando, G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09775-w · Cited by 245 · see citing works

A Pliable Mediator Acts as a Functional Rather Than an Architectural Bridge between Promoters and Enhancers

El Khattabi, L., Zhao, H., Kalchschmidt, J., Young, N., Jung, S., Van Blerkom, P., Kieffer-Kwon, P., Kieffer-Kwon, K.-R., Park, S., Wang, X., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.011 · Cited by 244 · see citing works

PRC1 catalytic activity is central to polycomb system function

Blackledge, N. P., Fursova, N. A., Kelley, J. R., Huseyin, M. K., Feldmann, A., & Klose, R. J. (2020) · Molecular Cell · doi:10.1016/j.molcel.2019.12.001 · Cited by 243 · see citing works

Dynamic Rewiring of Promoter-Anchored Chromatin Loops during Adipocyte Differentiation

Siersbæk, R., Madsen, J. G. S., Javierre, B. M., Nielsen, R., Bagge, E. K., Cairns, J., Wingett, S. W., Traynor, S., Spivakov, M., Fraser, P., et al. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.04.010 · Cited by 243 · see citing works

Identification of significant chromatin contacts from HiChIP data by FitHiChIP

Bhattacharyya, S., Chandra, V., Vijayanand, P., & Ay, F. (2019) · Nature Communications · doi:10.1038/s41467-019-11950-y · Cited by 238 · see citing works

Dynamic Reorganization of Extremely Long-Range Promoter-Promoter Interactions between Two States of Pluripotency

Joshi, O., Wang, S.-Y., Kuznetsova, T., Atlasi, Y., Peng, T., Fabre, P. J., Habibi, E., Shaik, J., Saeed, S., Handoko, L., et al. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.11.010 · Cited by 198 · see citing works

A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation

Vujkovic, M., Ramdas, S., Lorenz, K. M., Guo, X., Darlay, R., Cordell, H. J., He, J., Gindin, Y., Chung, C., Myers, R. P., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01078-z · Cited by 205 · see citing works

GenPipes: an open-source framework for distributed and scalable genomic analyses

Bourgey, M., Dali, R., Eveleigh, R. J. M., Chen, K. C., Létourneau, L., Fillon, J., Michaud, M., Caron, M., Sandoval, J., Lefebvre, F., et al. (2019) · GigaScience · doi:10.1093/gigascience/giz037 · Cited by 201 · see citing works

The reference epigenome and regulatory chromatin landscape of chronic lymphocytic leukemia

Beekman, R., Chapaprieta, V., Russiñol, N., Vilarrasa-Blasi, R., Verdaguer-Dot, N., Martens, J., Duran-Ferrer, M., Kulis, M., Serra, F., Javierre, B. M., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0028-4 · Cited by 185 · see citing works

Cohesin Disrupts Polycomb-Dependent Chromosome Interactions in Embryonic Stem Cells

Rhodes, J. D. P., Feldmann, A., Hernández-Rodríguez, B., Díaz, N., Brown, J. M., Fursova, N. A., Blackledge, N. P., Prathapan, P., Dobrinic, P., Huseyin, M. K., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2019.12.057 · Cited by 187 · see citing works

Systematic identification and characterization of regulatory elements derived from human endogenous retroviruses

Ito, J., Sugimoto, R., Nakaoka, H., YAMADA, S., Kimura, T., Hayano, T., & Inoue, I. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006883 · Cited by 179 · see citing works

Mapping cis-Regulatory Chromatin Contacts in Neural Cells Links Neuropsychiatric Disorder Risk Variants to Target Genes

Song, M., Yang, X.-Y., Ren, X.-J., Maliskova, L., Li, B.-K., Jones, I. R., Wang, C., Jacob, F., Wu, K. Y., Traglia, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0472-1 · Cited by 172 · see citing works

Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

Thiecke, M. J., Wutz, G., Muhar, M., Tang, W., Bevan, S., Malysheva, V., Stocsits, R., Neumann, T., Zuber, J., Fraser, P., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107929 · Cited by 177 · see citing works

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Waage, J., collaborators, A., Standl, M., Curtin, J. A., Jessen, L. E., Thorsen, J., Tian, C., Schoettler, N., Flores, C., Abdellaoui, A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0157-1 · Cited by 167 · see citing works

Measuring the reproducibility and quality of Hi-C data

Yardımcı, G. G., Özadam, H., Sauria, M. E. G., Ursu, O., Yan, K., Yang, T., Chakraborty, A., Kaul, A., Lajoie, B. R., Song, F., et al. (2019) · Genome biology · doi:10.1186/s13059-019-1658-7 · Cited by 171 · see citing works

A supervised learning framework for chromatin loop detection in genome-wide contact maps

Salameh, T. J., Wang, X., Song, F., Zhang, B., Wright, S. M., Khunsriraksakul, C., Ruan, Y., & Yue, F. (2020) · Nature Communications · doi:10.1038/s41467-020-17239-9 · Cited by 165 · see citing works

Global reorganisation of cis-regulatory units upon lineage commitment of human embryonic stem cells

Freire-Pritchett, P., Schoenfelder, S., Várnai, C., Wingett, S. W., Cairns, J., Collier, A. J., García-Vílchez, R., Furlan-Magaril, M., Osborne, C. S., Fraser, P., et al. (2017) · eLife · doi:10.7554/elife.21926 · Cited by 161 · see citing works

Mapping the epigenomic and transcriptomic interplay during memory formation and recall in the hippocampal engram ensemble

Marco, A., Meharena, H. S., Dileep, V., Raju, R. M., Davila-Velderrain, J., Zhang, A. L., Adaikkan, C., Young, J. Z., Gao, F., Kellis, M., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00717-0 · Cited by 159 · see citing works

HiCcompare: an R-package for joint normalization and comparison of HI-C datasets

Stansfield, J., Cresswell, K., Vladimirov, V., & Dozmorov, M. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2288-x · Cited by 127 · see citing works

Genome-scale Capture C promoter interactions implicate effector genes at GWAS loci for bone mineral density

Chesi, A., Wagley, Y., Johnson, M. E., Manduchi, E., Su, C., Lu, S., Leonard, M. E., Hodge, K. M., Pippin, J. A., Hankenson, K. D., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09302-x · Cited by 158 · see citing works

How best to identify chromosomal interactions: a comparison of approaches

Davies, J., Oudelaar, A. M., Higgs, D., & Hughes, J. R. (2017) · Nature Methods · doi:10.1038/nmeth.4146 · Cited by 133 · see citing works

A promoter interaction map for cardiovascular disease genetics

Montefiori, L. E., Sobreira, D. R., Sakabe, N. J., Aneas, I., Joslin, A. C., Hansen, G. T., Bozek, G., Moskowitz, I. P., McNally, E. M., & Nóbrega, M. A. (2018) · eLife · doi:10.7554/elife.35788 · Cited by 145 · see citing works

Inferring Interaction Networks From Multi-Omics Data

Hawe, J. S., Theis, F. J., & Heinig, M. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00535 · Cited by 139 · see citing works

GenomeDISCO: A concordance score for chromosome conformation capture experiments using random walks on contact map graphs

Ursu, O., Boley, N., Taranova, M., Wang, Y. X. R., Yardımcı, G., Noble, W. S., & Kundaje, A. (2017) · bioRxiv · doi:10.1093/bioinformatics/bty164 · Cited by 130 · see citing works

DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning

Li, W., Wong, W. H., & Jiang, R. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz167 · Cited by 135 · see citing works

Characterization of hundreds of regulatory landscapes in developing limbs reveals two regimes of chromatin foldingPreprint

Andrey, G., Schöpflin, R., Jerković, I., Heinrich, V., Ibrahim, D. M., Paliou, C., Hochradel, M., Timmermann, B., Haas, S. A., Vingron, M., et al. (2016) · Genome Research · doi:10.1101/gr.213066.116 · Cited by 122 · see citing works

Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor

Litchfield, K., Levy, M., Orlando, G., Loveday, C., Law, P., Migliorini, G., Holroyd, A., Broderick, P., Karlsson, R., Haugen, T. B., et al. (2017) · Nature Genetics · doi:10.1038/ng.3896 · Cited by 127 · see citing works

Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen

Li, Z., Kuppe, C., Ziegler, S. M., Cheng, M., Kabgani, N., Menzel, S., Zenke, M., Kramann, R., & Costa, I. G. (2021) · Nature Communications · doi:10.1038/s41467-021-26530-2 · Cited by 120 · see citing works

The state of play in higher eukaryote gene annotation

Mudge, J. M., & Harrow, J. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.119 · Cited by 122 · see citing works

Interferon inducible X-linked gene CXorf21 may contribute to sexual dimorphism in Systemic Lupus Erythematosus

Odhams, C. A., Roberts, A. L., Vester, S. K., Duarte, C., Beales, C. T., Clarke, A. J., Lindinger, S., Daffern, S. J., Zito, A., Chen, L., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10106-2 · Cited by 120 · see citing works

Condensin II Counteracts Cohesin and RNA Polymerase II in the Establishment of 3D Chromatin Organization

Rowley, M. J., Lyu, X., Rana, V., Ando‐Kuri, M., Karns, R., Bosco, G., & Corces, V. G. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.01.116 · Cited by 114 · see citing works

Long-Range Enhancer Interactions Are Prevalent in Mouse Embryonic Stem Cells and Are Reorganized upon Pluripotent State Transition

Novo, C. L., Javierre, B.-M., Cairns, J., Segonds-Pichon, A., Wingett, S. W., Freire-Pritchett, P., Furlan-Magaril, M., Schoenfelder, S., Fraser, P., & Rugg-Gunn, P. J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.040 · Cited by 119 · see citing works

TOP1 inhibition therapy protects against SARS-CoV-2-induced lethal inflammation

Ho, J., Mok, B. W.-Y., Campisi, L., Jordan, T. X., Yildiz, S., Parameswaran, S., Wayman, J. A., Gaudreault, N. N., Meekins, D. A., Indran, S. V., et al. (2021) · Cell · doi:10.1016/j.cell.2021.03.051 · Cited by 121 · see citing works

Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma

Went, M., Sud, A., Försti, A., Halvarsson, B.-M., Weinhold, N., Kimber, S. T., van Duin, M., Þorleifsson, G., Holroyd, A., Johnson, D. C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04989-w · Cited by 113 · see citing works

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

Schoenfelder, S., Javierre, B. M., Furlan-Magaril, M., Wingett, S., & Fraser, P. (2018) · Journal of Visualized Experiments · doi:10.3791/57320 · Cited by 114 · see citing works

A Dementia-Associated Risk Variant near TMEM106B Alters Chromatin Architecture and Gene Expression

Gallagher, M. D., Posavi, M., Huang, P., Unger, T. L., Berlyand, Y., Gruenewald, A. L., Chesi, A., Manduchi, E., Wells, A. D., Grant, S. F. A., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.09.004 · Cited by 109 · see citing works

High resolution genetic mapping of putative causal interactions between regions of open chromatin

Kumasaka, N., Knights, A., & Gaffney, D. (2018) · Nature Genetics · doi:10.1038/s41588-018-0278-6 · Cited by 99 · see citing works

Hi-C analysis: from data generation to integration

Pal, K., Forcato, M., & Ferrari, F. (2018) · Biophysical Reviews · doi:10.1007/s12551-018-0489-1 · Cited by 82 · see citing works

Highly interconnected enhancer communities control lineage-determining genes in human mesenchymal stem cells

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 94 · see citing works

Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS

Pan, D. Z., Garske, K. M., Alvarez, M., Bhagat, Y. V., Boocock, J., Nikkola, E., Miao, Z., Raulerson, C. K., Cantor, R. M., Civelek, M., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03554-9 · Cited by 93 · see citing works

Mapping effector genes at lupus GWAS loci using promoter Capture-C in follicular helper T cells

Su, C., Johnson, M. E., Torres, A., Thomas, R. M., Manduchi, E., Sharma, P. K., Mehra, P., Coz, C. L., Leonard, M. E., Lu, S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17089-5 · Cited by 91 · see citing works

Whole-genome sequencing of multiple myeloma reveals oncogenic pathways are targeted somatically through multiple mechanisms

Hoang, P. H., Dobbins, S. E., Cornish, A. J., Chubb, D., Law, P., Kaiser, M., & Houlston, R. S. (2018) · Leukemia · doi:10.1038/s41375-018-0103-3 · Cited by 87 · see citing works

TET-dependent regulation of retrotransposable elements in mouse embryonic stem cells

de la Rica, L., Deniz, Ö., Cheng, K. C. L., Todd, C. D., Cruz, C., Houseley, J. M., & Branco, M. R. (2016) · Genome biology · doi:10.1186/s13059-016-1096-8 · Cited by 89 · see citing works

Identification of four novel associations for B-cell acute lymphoblastic leukaemia risk

Vijayakrishnan, J., Qian, M., Studd, J. B., Yang, W., Kinnersley, B., Law, P., Broderick, P., Raetz, E. A., Allan, J. M., Pui, C., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13069-6 · Cited by 88 · see citing works

Spatial patterns of CTCF sites define the anatomy of TADs and their boundaries

Nanni, L., Ceri, S., & Logie, C. (2020) · Genome Biology · doi:10.1186/s13059-020-02108-x · Cited by 88 · see citing works

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

Carty, M., Zamparo, L., Şahin, M., González, Á., Pelossof, R., Elemento, O., & Leslie, C. S. (2017) · Nature Communications · doi:10.1038/ncomms15454 · Cited by 80 · see citing works

Increased enhancer–promoter interactions during developmental enhancer activation in mammals

Chen, Z., Snetkova, V., Bower, G., Jacinto, S. H., Clock, B., Dizehchi, A., Barozzi, I., Mannion, B. J., Alcaina‐Caro, A., López-Rı́os, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01681-2 · Cited by 84 · see citing works

Enhancer–promoter interactions become more instructive in the transition from cell-fate specification to tissue differentiation

Pollex, T., Rabinowitz, A. H., Gambetta, M. C., Marco-Ferreres, R., Viales, R. R., Jankowski, A., Schaub, C., & Furlong, E. E. M. (2024) · Nature Genetics · doi:10.1038/s41588-024-01678-x · Cited by 82 · see citing works

Multi-Omics Approaches in Immunological Research

Chu, X., Zhang, B., Koeken, V. A. C. M., Gupta, M. K., & Li, Y. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.668045 · Cited by 86 · see citing works

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 · see citing works

Global discovery of lupus genetic risk variant allelic enhancer activity

Lu, X., Chen, X., Forney, C. R., Donmez, O. A., Miller, D., Parameswaran, S., Hong, T., Huang, Y., Pujato, M. A., Cazares, T. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21854-5 · Cited by 74 · see citing works

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Burren, O. S., Rubio García, A., Javierre, B.-M., Rainbow, D. B., Cairns, J., Cooper, N. J., Lambourne, J. J., Schofield, E., Castro Dopico, X., Ferreira, R. C., et al. (2017) · Genome Biology · doi:10.1186/s13059-017-1285-0 · Cited by 80 · see citing works

Spatial Genome Re-organization between Fetal and Adult Hematopoietic Stem Cells

Chen, C.-Y., Yu, W.-B., Tober, J., Gao, P., He, B., Lee, K., Trieu, T., Blobel, G., Speck, N., & Tan, K. (2019) · bioRxiv · doi:10.1016/j.celrep.2019.11.065 · Cited by 65 · see citing works

Three-dimensional genome architecture and emerging technologies: looping in disease

Mishra, A., & Hawkins, R. (2017) · Genome Medicine · doi:10.1186/s13073-017-0477-2 · Cited by 72 · see citing works

Identification of 22 susceptibility loci associated with testicular germ cell tumors

Pluta, J. B., Pyle, L. C., Nead, K. T., Wilf, R., Li, M., Mitra, N., Weathers, B., D'Andrea, K. P., Almstrup, K., Anson‐Cartwright, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24334-y · Cited by 74 · see citing works

diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data

Lareau, C. A., & Aryee, M. J. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx623 · Cited by 72 · see citing works

Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer

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 73 · see citing works

Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

Yang, J., McGovern, A., Martin, P., Duffus, K., Ge, X. J., Zarrineh, P., Morris, A. P., Adamson, A. D., Fraser, P., Rattray, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18180-7 · Cited by 71 · see citing works

Promoter interactome of human embryonic stem cell-derived cardiomyocytes connects GWAS regions to cardiac gene networks

Choy, M., Javierre, B. M., Williams, S. G., Baross, S. L., Liu, Y., Wingett, S., Akbarov, A., Wallace, C., Freire-Pritchett, P., Rugg‐Gunn, P. J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04931-0 · Cited by 72 · see citing works

The transcription factor NF-κB orchestrates nucleosome remodeling during the primary response to Toll-like receptor 4 signaling

Feng, A., Thomas, B. J., Purbey, P. K., de Melo, F. M., Liu, X., Daly, A. E., Sun, F., Lo, J. H.-H., Cheng, L., Carey, M., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.02.004 · Cited by 69 · see citing works

Biological constraints on GWAS SNPs at suggestive significance thresholds reveal additional BMI loci

Hammond, R. K., Pahl, M. C., Su, C., Cousminer, D. L., Leonard, M. E., Lu, S., Doege, C. A., Wagley, Y., Hodge, K. M., Lasconi, C., et al. (2021) · eLife · doi:10.7554/elife.62206 · Cited by 68 · see citing works

Alterations in promoter interaction landscape and transcriptional network underlying metabolic adaptation to diet

Qin, Y., Grimm, S. A., Roberts, J. D., Chrysovergis, K., & Wade, P. A. (2020) · Nature Communications · doi:10.1038/s41467-020-14796-x · Cited by 67 · see citing works

DeepLoop robustly maps chromatin interactions from sparse allele-resolved or single-cell Hi-C data at kilobase resolution

Zhang, S., Plummer, D., Lu, L., Cui, J., Xu, W., Wang, M., Liu, X., Prabhakar, N., Shrinet, J., Srinivasan, D., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01116-w · Cited by 63 · see citing works

Epigenetic modulation of a hardwired 3D chromatin landscape in two naive states of pluripotency

Atlasi, Y., Megchelenbrink, W., Peng, T., Habibi, E., Joshi, O., Wang, S.-Y., Wang, C., Logie, C., Poser, I., Marks, H., et al. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0310-9 · Cited by 66 · see citing works

CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets

Schofield, E. C., Carver, T., Achuthan, P., Freire-Pritchett, P., Spivakov, M., Todd, J. A., & Burren, O. S. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw173 · Cited by 65 · see citing works

Aberrant activation of m6A demethylase FTO renders HIF2α low/− clear cell renal cell carcinoma sensitive to BRD9 inhibitors

Zhang, C., Chen, L., Lou, W., Su, J., Huang, J., Liu, A., Xu, Y., He, H., Gao, Y., Xu, D., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abf6045 · Cited by 66 · see citing works

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity

Pancaldi, V., Pau, E. C. D. S., Javierre, B. M., Juan, D., Fraser, P., Spivakov, M., Valencia, A., & Rico, D. (2015) · Genome Biology · doi:10.1186/s13059-016-1003-3 · Cited by 59 · see citing works

Capture-C: A modular and flexible approach for high-resolution chromosome conformation capture

Downes, D., Smith, A. L., Karpińska, M. A., Velychko, T., Rue-Albrecht, K., Sims, D., Milne, T., Davies, J., Oudelaar, A. M., & Hughes, J. (2022) · Nature Protocols · doi:10.1038/s41596-021-00651-w · Cited by 52 · see citing works

Determining chromatin architecture with Micro Capture-C

Hamley, J. C., Li, H.-P., Denny, N., Downes, D., & Davies, J. O. J. (2023) · Nature Protocols · doi:10.1038/s41596-023-00817-8 · Cited by 49 · see citing works

Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver

Çalışkan, M., Manduchi, E., Rao, H. S., Segert, J. A., Beltrame, M. H., Trizzino, M., Park, Y., Baker, S. W., Chesi, A., Johnson, M. E., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.05.010 · Cited by 57 · see citing works

Aged intestinal stem cells propagate cell-intrinsic sources of inflammaging in mice

Funk, M. C., Gleixner, J., Heigwer, F., Vonficht, D., Valentini, E., Aydin, Z., Tonin, E., Prete, S., Mahara, S., Throm, Y., et al. (2023) · Developmental Cell · doi:10.1016/j.devcel.2023.11.013 · Cited by 60 · see citing works

Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model

Wilson, N. K., Schoenfelder, S., Hannah, R., Castillo, M. S., Schütte, J., Ladopoulos, V., Mitchelmore, J., Goode, D. K., Calero‐Nieto, F. J., Moignard, V., et al. (2016) · Blood · doi:10.1182/blood-2015-10-677393 · Cited by 57 · see citing works

Platelet function is modified by common sequence variation in megakaryocyte super enhancers

Petersen, R., Lambourne, J. J., Javierre, B. M., Grassi, L., Kreuzhuber, R., Ruklisa, D., Rosa, I. M., Tomé, A. R., Elding, H., van Geffen, J. P., et al. (2017) · Nature Communications · doi:10.1038/ncomms16058 · Cited by 58 · see citing works

Divergent wiring of repressive and active chromatin interactions between mouse embryonic and trophoblast lineages

Schoenfelder, S., Mifsud, B., Senner, C. E., Todd, C. D., Chrysanthou, S., Darbo, E., Hemberger, M., & Branco, M. R. (2018) · Nature Communications · doi:10.1038/s41467-018-06666-4 · Cited by 54 · see citing works

Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease

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 · see citing works

A model of active transcription hubs that unifies the roles of active promoters and enhancers

Zhu, I., Song, W., Ovcharenko, I., & Landsman, D. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab235 · Cited by 55 · see citing works

Sugar Beet Breeding

McGrath, J. M., & Panella, L. W. (2018) · Plant breeding reviews · doi:10.1002/9781119521358.ch5 · Cited by 55 · see citing works

Genome-wide association study of response to methotrexate in early rheumatoid arthritis patients

MATURA, O. B. O. T., Taylor, J., PAMERA, A., Consortia, Bongartz, T., Massey, J., Mifsud, B., Spiliopoulou, A., Scott, I. C., Wang, J., et al. (2018) · The Pharmacogenomics Journal · doi:10.1038/s41397-018-0025-5 · Cited by 52 · see citing works

Transcriptional decomposition reveals active chromatin architectures and cell specific regulatory interactions

Rennie, S., Dalby, M., van Duin, L., & Andersson, R. (2018) · Nature Communications · doi:10.1038/s41467-017-02798-1 · Cited by 50 · see citing works

Selfish: discovery of differential chromatin interactions via a self-similarity measure

Ardakany, A. R., Ay, F., & Lonardi, S. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz362 · Cited by 52 · see citing works

Altered chromatin landscape and enhancer engagement underlie transcriptional dysregulation in MED12 mutant uterine leiomyomas

Moyo, M., Parker, J. B., & Chakravarti, D. (2020) · Nature Communications · doi:10.1038/s41467-020-14701-6 · Cited by 51 · see citing works

Dynamic CpG methylation delineates subregions within super-enhancers selectively decommissioned at the exit from naive pluripotency

Bell, E., Curry, E. W., Megchelenbrink, W., Jouneau, L., Brochard, V., Tomaz, R. A., Mau, K. H. T., Atlasi, Y., de Souza, R. A., Marks, H., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14916-7 · Cited by 49 · see citing works

Widespread reorganisation of pluripotent factor binding and gene regulatory interactions between human pluripotent states

Chovanec, P., Collier, A. J., Krueger, C., Várnai, C., Semprich, C. I., Schoenfelder, S., Corcoran, A. E., & Rugg‐Gunn, P. J. (2021) · Nature Communications · doi:10.1038/s41467-021-22201-4 · Cited by 48 · see citing works

Analysis of 3D genomic interactions identifies candidate host genes that transposable elements potentially regulate

Raviram, R., Rocha, P. P., Luo, V. M., Swanzey, E., Miraldi, E. R., Chuong, E. B., Feschotte, C., Bonneau, R., & Skok, J. A. (2018) · Genome biology · doi:10.1186/s13059-018-1598-7 · Cited by 50 · see citing works

Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation

Zhang, Y., & Hardison, R. C. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx659 · Cited by 47 · see citing works

Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

Sud, A., Thomsen, H., Law, P., Försti, A., Filho, M. I. D. S., Holroyd, A., Broderick, P., Orlando, G., Lenive, O., Wright, L. B., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00320-1 · Cited by 49 · see citing works

Variant-to-gene mapping followed by cross-species genetic screening identifies GPI-anchor biosynthesis as a regulator of sleep

Palermo, J., Chesi, A., Zimmerman, A. J., Sonti, S., Pahl, M. C., Lasconi, C., Brown, E., Pippin, J. A., Wells, A. D., Doldur-Balli, F., et al. (2023) · Science Advances · doi:10.1126/sciadv.abq0844 · Cited by 47 · see citing works

Transcriptionally active enhancers in human cancer cells

Lidschreiber, K., Jung, L. A., von der Emde, H., Dave, K., Taipale, J., Cramer, P., & Lidschreiber, M. (2021) · Molecular Systems Biology · doi:10.15252/msb.20209873 · Cited by 44 · see citing works

Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools

Freire-Pritchett, P., Ray-Jones, H., Rosa, M. D., Eijsbouts, C., Orchard, W. R., Wingett, S., Wallace, C., Cairns, J. M., Spivakov, M., & Malysheva, V. (2021) · Nature Protocols · doi:10.1038/s41596-021-00567-5 · Cited by 34 · see citing works

Additional file 3: of CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Cairns, J., Freire-Pritchett, P., Wingett, S., Vรกrnai, C., Dimond, A., Plagnol, V., Zerbino, D. R., Schoenfelder, S., Javierre, B.-M., Osborne, C. S., et al. (2016) · Figshare · doi:10.6084/m9.figshare.4340768

Additional file 1: of CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Cairns, J., Freire-Pritchett, P., Wingett, S., Vรกrnai, C., Dimond, A., Plagnol, V., Zerbino, D., Schoenfelder, S., Javierre, B.-M., Osborne, C., et al. (2016) · Figshare · doi:10.6084/m9.figshare.c.3603770_d3

Additional file 2: of CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Cairns, J., Freire-Pritchett, P., Wingett, S., Vรกrnai, C., Dimond, A., Plagnol, V., Zerbino, D., Schoenfelder, S., Javierre, B.-M., Osborne, C. S., et al. (2016) · Figshare · doi:10.6084/m9.figshare.c.3603770_d1

Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data

Cairns, J., Orchard, W. R., Malysheva, V., & Spivakov, M. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz450 · Cited by 28 · see citing works