ChAsE: chromatin analysis and exploration tool
Open accessAbstract
: We present ChAsE, a cross-platform desktop application developed for interactive visualization, exploration and clustering of epigenomic data such as ChIP-seq experiments. ChAsE is designed and developed in close collaboration with several groups of biologists and bioinformaticians with a focus on usability and interactivity. Data can be analyzed through k-means clustering, specifying presence or absence of signal in epigenetic data and performing set operations between clusters. Results can be explored in an interactive heat map and profile plot interface and exported for downstream analysis or as high quality figures suitable for publications. AVAILABILITY AND IMPLEMENTATION: Software, source code (MIT License), data and video tutorials available at http://chase.cs.univie.ac.at CONTACT: : mkarimi@brc.ubc.ca or torsten.moeller@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.
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K-means clustering (K=5) on HNF4A and FOXA2 bound regions identified 5 clusters, with large overlap between HBRs and FBRs (Cl2, Cl3, Cl4) and two clusters showing exclusive binding of either HNF4A or FOXA2 (Cl1 and Cl5).
“To address this, we performed K-means clustering (K=5) on HNF4A and FOXA2 bound regions in hepatocytes using ChAsE (35) and identified 5 clusters. As expected, a large overlap was observed between HBRs and FBRs (Cl2, Cl3 and Cl4), however, two clusters showed exclusive binding of either HNF4A or FOXA2 (Cl1 and Cl5, respectively) (Fig. 2A).”
From Hepatocyte Nuclear Factor 4‐Alpha Is Essential for the Active Epigenetic State at Enhancers in Mouse Liver (2019) · cites this paper as [35]
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Cites
Discovery and characterization of chromatin states for systematic annotation of the human genome
Ernst, J., & Kellis, M. (2010) · Nature Biotechnology · doi:10.1038/nbt.1662 · Cited by 1,033 · see citing works
Base-Resolution Analysis of 5-Hydroxymethylcytosine in the Mammalian Genome
Yu, M., Hon, G. C., Szulwach, K. E., Song, C., Zhang, L., Kim, A., Li, X., Dai, Q., Shen, Y., Park, B., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.027 · Cited by 1,022 · see citing works
Cistrome: an integrative platform for transcriptional regulation studies
Liu, T., Ortiz, J. A., Taing, L., Meyer, C. A., Lee, B. T. K., Zhang, Y., Shin, H., Wong, S. S., Ma, J., Lei, Y., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-8-r83 · Cited by 705 · see citing works
Karimi, M. M., Goyal, P., Maksakova, I. A., Bilenky, M., Leung, D., Tang, J. X., Shinkai, Y., Mager, D. L., Jones, S., Hirst, M., et al. (2011) · Cell Stem Cell · doi:10.1016/j.stem.2011.04.004 · Cited by 535 · see citing works
Self-citationThe Human Epigenome Browser at Washington University
Zhou, X., Maricque, B. B., Xie, M., Li, D., Sundaram, V., Martin, E. A., Koebbe, B. C., Nielsen, C. B., Hirst, M., Farnham, P., et al. (2011) · Nature Methods · doi:10.1038/nmeth.1772 · Cited by 309 · see citing works
Self-citationFejes, A. P., Robertson, G., Bilenky, M., Varhol, R., Bainbridge, M., & Jones, S. J. M. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn305 · Cited by 272 · see citing works
Self-citationChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome
Hon, G. C., Ren, B., & Wang, W. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000201 · Cited by 152 · see citing works
Epiviz: interactive visual analytics for functional genomics data
Chelaru, F., Smith, L., Goldstein, N., & Bravo, H. C. (2014) · Nature Methods · doi:10.1038/nmeth.3038 · Cited by 61 · see citing works
Spark: A navigational paradigm for genomic data explorationPreprint
Nielsen, C. B., Younesy, H., O’Geen, H., Xu, X., Jackson, A. R., Milosavljevic, A., Wang, T., Costello, J., Hirst, M., Farnham, P., et al. (2012) · Genome Research · doi:10.1101/gr.140665.112 · Cited by 35 · see citing works
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Harutyunyan, A. S., Krug, B., Chen, H., Papillon‐Cavanagh, S., Zeinieh, M. P., Jay, N. D., Deshmukh, S., Chen, C. C. L., Belle, J. I., Mikael, L. G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09140-x · Cited by 348 · see citing works
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Xu, Y., Huangyang, P., Wang, Y., Xue, L., Devericks, E. N., Nguyen, H. G., Yu, X., Osés-Prieto, J. A., Burlingame, A. L., Miglani, S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.036 · Cited by 166 · see citing works
Marques, C., Unterkircher, T., Kroon, P., Oldrini, B., Izzo, A., Dramaretska, Y., Ferrarese, R., Kling, E., Schnell, O., Nelander, S., et al. (2021) · eLife · doi:10.7554/elife.64846 · Cited by 115 · see citing works
Brind’Amour, J., Kobayashi, H., Albert, J. R., Shirane, K., Sakashita, A., Kamio, A., Bogutz, A., Koike, T., Karimi, M. M., Lefebvre, L., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05841-x · Cited by 105 · see citing works
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Trizzino, M., Barbieri, E., Petracovici, A., Wu, S., Welsh, S. A., Owens, T. A., Licciulli, S., Zhang, R., & Gardini, A. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.05.097 · Cited by 97 · see citing works
Judson, R. N., Quarta, M., Oudhoff, M. J., Soliman, H. S., Yi, L., Chang, C. K., Loi, G., Werff, R. V., Cait, A., Hamer, M., et al. (2018) · Cell stem cell · doi:10.1016/j.stem.2017.12.010 · Cited by 86 · see citing works
Self-citationThakur, A., Wong, J. C. H., Wang, E. Y., Lotto, J., Kim, D., Cheng, J., Mingay, M., Cullum, R., Moudgil, V., Ahmed, N., et al. (2019) · Hepatology · doi:10.1002/hep.30631 · Cited by 75 · see citing works
“To address this, we performed K-means clustering (K = 5) on HBRs and FBRs in hepatocytes using ChAsE(35) and identified five clusters.”
MethodInfluentialSelf-citationTargeted Enhancer Activation by a Subunit of the Integrator Complex
Barbieri, E., Trizzino, M., Welsh, S. A., Owens, T. A., Calabretta, B., Carroll, M. P., Sarma, K., & Gardini, A. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.05.031 · Cited by 71 · see citing works
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Marunde, M. R., Fuchs, H. A., Burg, J. M., Popova, I. K., Vaidya, A., Hall, N. W., Weinzapfel, E. N., Meiners, M. J., Watson, R., Gillespie, Z. B., et al. (2024) · eLife · doi:10.7554/elife.78866 · Cited by 65 · see citing works
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Vainshtein, Y., Rippe, K., & Teif, V. B. (2017) · BMC Genomics · doi:10.1186/s12864-017-3580-2 · Cited by 44 · see citing works
Huo, D., Chen, H., Cheng, Y., Song, X., Zhang, K., Li, M. J., & Xuan, C. (2019) · Cell Death and Differentiation · doi:10.1038/s41418-019-0397-3 · Cited by 43 · see citing works
Hemming, M. L., Benson, M. R., Loycano, M. A., Anderson, J. A., Andersen, J. L., Taddei, M. L., Krivtsov, A. V., Aubrey, B. J., Cutler, J. A., Hatton, C., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0646 · Cited by 44 · see citing works
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Broche, J., Kungulovski, G., Bashtrykov, P., Rathert, P., & Jeltsch, A. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1169 · Cited by 38 · see citing works
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Ren, W., Medeiros, N., Warneford-Thomson, R., Wulfridge, P., Yan, Q., Bian, J., Sidoli, S., Garcia, B., Skordalakes, E., Joyce, E., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15902-9 · Cited by 27 · see citing works
Hemming, M. L., Lawlor, M. A., Andersen, J. L., Hagan, T., Chipashvili, O., Scott, T. G., Raut, C. P., Sicińska, E., Armstrong, S. A., Demetri, G. D., et al. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-1888 · Cited by 32 · see citing works
Numata, A., Kwok, H.-S., Kawasaki, A., Li, J., Zhou, Q.-L., Kerry, J., Benoukraf, T., Bararia, D., Li, F., Ballabio, E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03854-0 · Cited by 28 · see citing works
Lee, E., Wongvipat, J., Choi, D., Wang, P., Lee, Y. S., Zheng, D., Watson, P. A., Gopalan, A., & Sawyers, C. L. (2019) · eLife · doi:10.7554/elife.41913 · Cited by 26 · see citing works
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Papin, C., Gras, S. L., Ibrahim, A., Salem, H., Karimi, M. M., Stoll, I., Ugrinova, I., Schröder, M., Fontaine, E., Omran, Z., et al. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.09.018 · Cited by 25 · see citing works
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Lemma, R. B., Ledsaak, M., Fuglerud, B. M., Sandve, G. K., Eskeland, R., & Gabrielsen, O. S. (2021) · Scientific Reports · doi:10.1038/s41598-021-88516-w · Cited by 17 · see citing works
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Blanco, E., González-Ramírez, M., & Croce, L. D. (2021) · Scientific Reports · doi:10.1038/s41598-021-98889-7 · Cited by 17 · see citing works
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Choudalakis, M., Kungulovski, G., Mauser, R., Bashtrykov, P., & Jeltsch, A. (2023) · Protein Science · doi:10.1002/pro.4760 · Cited by 14 · see citing works
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Thakur, A., Park, K., Cullum, R., Fuglerud, B. M., Khoshnoodi, M., Drissler, S., Stephan, T. L., Lotto, J., Kim, D., Gonzalez, F. J., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-05835-0 · Cited by 10 · see citing works
Duan, Y., Zhang, X., Yang, L., Xu, D., Zheng, Z., Cheng, Y., Chen, H., Lan, B., Li, D., Zhou, J., et al. (2019) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2019.11.008 · Cited by 10 · see citing works
Wei, L. K., & Au, A. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-805388-1.00012-2 · Cited by 8 · see citing works
Marques, C., Unterkircher, T., Kroon, P., Izzo, A., Dramaretska, Y., Kling, E., Oldrini, B., Schnell, O., Nelander, S., Wagner, E. F., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/834531 · Cited by 8 · see citing works
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Weekes, C., Willerding, L., Khadayate, S. P., Liebl, K., Mossler, A., Montoya, A., Rauthe, V., Karimi, M. M., Zacharias, M., Ulrich, H. D., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-75695-1 · Cited by 3 · see citing works
Self-citationChoudalakis, M., Bashtrykov, P., & Jeltsch, A. (2024) · Mobile DNA · doi:10.1186/s13100-024-00315-y · Cited by 3 · see citing works
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Girgis, H. Z., Velasco, A., & Reyes, Z. E. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2312-1 · Cited by 3 · see citing works
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Stephan, T. L., Cullum, R., Drissler, S., Thomas, A., Fuglerud, B. M., Clement-Ranney, M., Lotto, J., Krentz, N. A. J., Duncan, S. A., & Hoodless, P. A. (2025) · Developmental Cell · doi:10.1016/j.devcel.2025.05.014 · Cited by 1 · see citing works
Fullstone, T. L., Fischer, L. F. J., Bohmeier, M., Frings‐Meuthen, P., Crucian, B. E., & Rathert, P. (2025) · Scientific Reports · doi:10.1038/s41598-025-17930-1 · Cited by 1 · see citing works
Huse, J. T. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735362758.793558436
Identification of FLYWCH1 as a regulator of platinum-resistance in epithelial ovarian cancer
Fullstone, T. L., Rohm, H., Kaltofen, T., Hierlmayer, S., Reichenbach, J., Schweikert, S., Knodel, F., Loeffler, A.-K., Mayr, D. C., Jeschke, U., et al. (2025) · NAR Cancer · doi:10.1093/narcan/zcaf012
Girolamo, D. D., Urciuoli, G., Sol, S., Ferniani, M., Antonini, D., Marchese, E., Stefano, M. A. D., Baltissen, M. P. A., Ros, M. A., Dixon, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.24.661308
Choudalakis, M., Bashtrykov, P., & Jeltsch, A. (2024) · Figshare · doi:10.6084/m9.figshare.25538624
Choudalakis, M., Bashtrykov, P., & Jeltsch, A. (2024) · Figshare · doi:10.6084/m9.figshare.26701657
Choudalakis, M., Bashtrykov, P., & Jeltsch, A. (2024) · Figshare · doi:10.6084/m9.figshare.25538515
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Girolamo, D. D., Urciuoli, G., Sol, S., Ferniani, M., Antonini, D., Marchese, E., Palumbo, S., Stefano, M. A. D., Baltissen, M. P. A., Ros, M. A., et al. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.12.045
- Authors
- Younesy, H., Nielsen, C. B., Lorincz, M. C., Jones, S. J. M., Karimi, M. M., & Möller, T.
- Affiliations
- University of British Columbia (CA)
- BC Cancer Agency (CA)
- University of Vienna (AT)
- Corresponding author
- Karimi, Mohammad M.
- Möller, Torsten
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-07-04
- Volume
- 32
- Issue
- 21
- Pages
- 3324-3326
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC5079470
- OpenAlex
- W2467728588
- Cited by
- 41
- References
- 9
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 8 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 3 · 2019: 8 · 2018: 7 · 2017: 2
- FWCI
- 2.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Bioinformatics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Canadian Institutes of Health Research (20R91610)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- chase, ChIP-seq, K-means clustering, data exploration tools, desktop application, usability, bioinformatics software
- MeSH terms
- Animals, Chromatin, Humans, Programming Languages, Software, Cluster Analysis
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