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Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications
Open accessAbstract
Summary: A combination of bisulfite treatment of DNA and high-throughput sequencing (BS-Seq) can capture a snapshot of a cell's epigenomic state by revealing its genome-wide cytosine methylation at single base resolution. Bismark is a flexible tool for the time-efficient analysis of BS-Seq data which performs both read mapping and methylation calling in a single convenient step. Its output discriminates between cytosines in CpG, CHG and CHH context and enables bench scientists to visualize and interpret their methylation data soon after the sequencing run is completed. Availability and implementation: Bismark is released under the GNU GPLv3+ licence. The source code is freely available from www.bioinformatics.bbsrc.ac.uk/projects/bismark/. Contact: felix.krueger@bbsrc.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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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
Human DNA methylomes at base resolution show widespread epigenomic differences
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009) · Nature · doi:10.1038/nature08514 · Cited by 4,673
Conservation and divergence of methylation patterning in plants and animals
Feng, S., Cokus, S. J., Zhang, X., Chen, P.-Y., Bostick, M., Goll, M. G., Hetzel, J., Jain, J., Strauss, S. H., Halpern, M. E., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002720107 · Cited by 1,285
Research works printed but not linked: 6
- Chen, 2010, BS Seeker: precise mapping for bisulfite sequencing, BMC Bioinformatics, 11, 203, 10.1186/1471-2105-11-203 · DOI · Paper page
- Cokus, 2008, Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning, Nature, 452, 215, 10.1038/nature06745 · DOI · Paper page
- Harris, 2010, Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications, Nat. Biotechnol., 28, 1097, 10.1038/nbt.1682 · DOI · Paper page
- Law, 2010, Establishing, maintaining and modifying DNA methylation patterns in plants and animals, Nat. Rev. Genet., 11, 204, 10.1038/nrg2719 · DOI · Paper page
- Popp, 2010, Genome-wide erasure of DNA methylation in mouse primordial germ cells is affected by AID deficiency, Nature, 463, 1101, 10.1038/nature08829 · DOI · Paper page
- Robertson, 2005, DNA methylation and human disease, Nat. Rev. Genet., 6, 597, 10.1038/nrg1655 · DOI · Paper page
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Kerepesi, C., Zhang, B., Lee, S.-G., Trapp, A., & Gladyshev, V. N. (2021) · Science Advances · doi:10.1126/sciadv.abg6082 · Cited by 130
Sailani, M. R., Halling, J. F., Møller, H. D., Lee, H., Plomgaard, P., Pilegaard, H., Snyder, M. P., & Regenberg, B. (2019) · Scientific Reports · doi:10.1038/s41598-018-37895-8 · Cited by 129
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Xie, W., Kagiampakis, I., Pan, L., Zhang, Y. W., Murphy, L., Tao, Y., Kong, X., Kang, B., Xia, L., Carvalho, F. L. F., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.01.008 · Cited by 122
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Hayes, C. N., Nakahara, H., Ono, A., Tsuge, M., & Oka, S. (2024) · Genes · doi:10.3390/genes15121551 · Cited by 119
Pachano, T., Sánchez-Gaya, V., Ealo, T., Mariner-Faulí, M., Bleckwehl, T., Asenjo, H. G., Respuela, P., Cruz-Molina, S., Muñoz-San Martín, M., Haro, E., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00888-x · Cited by 116
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Lee, D.-S., Shin, J.-Y., Tonge, P. D., Puri, M. C., Lee, S., Park, H., Lee, W.-C., Hussein, S. M. I., Bleazard, T., Yun, J.-Y., et al. (2014) · Nature Communications · doi:10.1038/ncomms6619 · Cited by 113
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Epigenetic maintenance of topological domains in the highly rearranged gibbon genome
Lazar, N. H., Nevonen, K. A., O'Connell, B., McCann, C., O'Neill, R. J., Green, R. E., Meyer, T. J., Okhovat, M., & Carbone, L. (2018) · Genome Research · doi:10.1101/gr.233874.117 · Cited by 107
TET2 Regulates the Neuroinflammatory Response in Microglia
Carrillo-Jimenez, A., Deniz, Ö., Niklison-Chirou, M. V., Ruiz, R., Bezerra-Salomão, K., Stratoulias, V., Amouroux, R., Yip, P. K., Vilalta, A., Cheray, M., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.09.013 · Cited by 104
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Maze, I., Shen, L., Zhang, B., Garcia, B. A., Shao, N., Mitchell, A., Sun, H., Akbarian, S., Allis, C. D., & Nestler, E. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3816 · Cited by 100
Serpeloni, F., Radtke, K., de Assis, S. G., Henning, F., Nätt, D., & Elbert, T. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.153 · Cited by 98
Epigenetic Regulation of the Kappa Opioid Receptor by Child Abuse
Lutz, P.-E., Gross, J. A., Dhir, S. K., Maussion, G., Yang, J., Bramoulle, A., Meaney, M. J., & Turecki, G. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.07.012 · Cited by 96
McClatchy, J., Strogantsev, R., Wolfe, E., Lin, H. Y., Mohammadhosseini, M., Davis, B. A., Eden, C., Goldman, D., Fleming, W. H., Conley, P., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43697-y · Cited by 95
Impact of constitutional TET2 haploinsufficiency on molecular and clinical phenotype in humans
Kaasinen, E., Kuismin, O., Rajamäki, K., Ristolainen, H., Aavikko, M., Kondelin, J., Saarinen, S., Berta, D. G., Katainen, R., Hirvonen, E. A. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09198-7 · Cited by 92
Lee, S. C., Adams, D. W., Ipsaro, J. J., Cahn, J., Lynn, J., Kim, H.-S., Berube, B., Major, V., Calarco, J. P., LeBlanc, C., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.001 · Cited by 89
Extensive Recovery of Embryonic Enhancer and Gene Memory Stored in Hypomethylated Enhancer DNA
Jadhav, U., Cavazza, A., Banerjee, K. K., Xie, H., O’Neill, N. K., Saenz-Vash, V., Herbert, Z., Madha, S., Orkin, S. H., Zhai, H., et al. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.02.024 · Cited by 86
Peng, T., Zhai, Y., Atlasi, Y., ter Huurne, M., Marks, H., Stunnenberg, H. G., & Megchelenbrink, W. (2020) · Genome Biology · doi:10.1186/s13059-020-02156-3 · Cited by 83
Krebs, A. R., Dessus-Babus, S., Burger, L., & Schübeler, D. (2014) · eLife · doi:10.7554/elife.04094 · Cited by 81
Cooperative binding between distant transcription factors is a hallmark of active enhancers
Rao, S., Ahmad, K., & Ramachandran, S. (2021) · Molecular Cell · doi:10.1016/j.molcel.2021.02.014 · Cited by 82
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Ortega, M. A., Poirion, O., Zhu, X., Huang, S., Wolfgruber, T. K., Sebra, R., & Garmire, L. X. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0177-y · Cited by 81
In vitro reconstitution of epigenetic reprogramming in the human germ line
Murase, Y., Yokogawa, R., Yabuta, Y., Nagano, M., Katou, Y., Mizuyama, M., Kitamura, A., Puangsricharoen, P., Yamashiro, C., Hu, B., et al. (2024) · Nature · doi:10.1038/s41586-024-07526-6 · Cited by 80
Saggau, C., Bacher, P., Esser, D., Rasa, M., Meise, S., Mohr, N., Kohlstedt, N., Hutloff, A., Schacht, S.-S., Dargvainiene, J., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.08.005 · Cited by 79
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Zhang, Z., Zhou, J., Tan, P., Pang, Y., Rivkin, A., Kirchgessner, M. A., Williams, E., Lee, C.-T., Liu, H., Franklin, A. D., et al. (2020) · doi:10.1101/2020.04.01.019612 · Cited by 75
Kundu, P., Torres, E. R. S., Stagaman, K., Kasschau, K., Okhovat, M., Holden, S., Ward, S., Nevonen, K. A., Davis, B. A., Saito, T., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-83851-4 · Cited by 75
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Zhou, B., Ho, S. S., Greer, S. U., Spies, N., Bell, J. M., Zhang, X., Zhu, X., Arthur, J. G., Byeon, S., Pattni, R., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz169 · Cited by 72
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Huang, Y., Li, L., An, G., Yang, X., Cui, M., Song, X., Lin, J., Zhang, X., Yao, Z., Wan, C., et al. (2023) · Nature Cell Biology · doi:10.1038/s41556-023-01232-7 · Cited by 59
Saeki, K., Pan, R., Lee, E., Kurotaki, D., & Ozato, K. (2024) · Nature Immunology · doi:10.1038/s41590-024-01962-2 · Cited by 55
Taguchi, J., Shibata, H., Kabata, M., Kato, M., Fukuda, K., Tanaka, A., Ohta, S., Ukai, T., Mitsunaga, K., Yamada, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25249-4 · Cited by 46
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Mozgova, I., Wildhaber, T., Trejo‐Arellano, M. S., Fajkus, J., Roszak, P., Köhler, C., & Hennig, L. (2018) · New Phytologist · doi:10.1111/nph.15082 · Cited by 37
Stanojević, D., Li, Z., Bakić, S., Foo, R., & Šikić, M. (2024) · Nature Communications · doi:10.1038/s41467-024-49847-0 · Cited by 35
Hagemann, M., Gärtner, K., Scharnagl, M., Bolay, P., Lott, S. C., Fuss, J., Huettel, B., Reinhardt, R., Klähn, S., & Hess, W. R. (2018) · DNA Research · doi:10.1093/dnares/dsy006 · Cited by 34
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Awasthi, S., Tompkins, J., Singhal, J., Riggs, A. D., Yadav, S., Wu, X., Singh, S., Warden, C., Liu, Z., Wang, J., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1719586115 · Cited by 33
Discovery of cytosine deaminases enables base-resolution methylome mapping using a single enzyme
Vaisvila, R., Johnson, S. R., Yan, B., Dai, N., Bourkia, B. M., Chen, M., Corrêa, I. R., Yigit, E., & Sun, Z. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.01.027 · Cited by 32
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Viner, C., Ishak, C. A., Johnson, J., Walker, N. J., Shi, H., Sjöberg-Herrera, M. K., Shen, S. Y., Lardo, S. M., Adams, D. J., Ferguson-Smith, A. C., et al. (2024) · Genome Biology · doi:10.1186/s13059-023-03070-0 · Cited by 30
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Liu, D., Mu, Q., Li, X., Xu, S., Li, Y., & Gu, T. (2022) · Horticulture Research · doi:10.1093/hr/uhab073 · Cited by 29
Daron, J., & Slotkin, R. K. (2017) · Genome Biology · doi:10.1186/s13059-017-1232-0 · Cited by 29
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Hu, Y., An, Q., Guo, Y., Zhong, J., Fan, S., Rao, P., Liu, X., Liu, Y., & Fan, G. (2019) · Methods in Molecular Biology · doi:10.1007/978-1-4939-9240-9_21 · Cited by 26
Alisch, R. S., Van Hulle, C., Chopra, P., Bhattacharyya, A., Zhang, S.-C., Davidson, R. J., Kalin, N. H., & Goldsmith, H. H. (2017) · Translational Psychiatry · doi:10.1038/s41398-017-0047-9 · Cited by 25
Goodson, J. M., Weldy, C. S., MacDonald, J. W., Liu, Y., Bammler, T. K., Chien, W., & Chin, M. T. (2017) · The FASEB Journal · doi:10.1096/fj.201700032r · Cited by 25
Cao, Y., Yang, H., Jin, L., Du, J., & Fan, Z. (2018) · Stem Cells International · doi:10.1155/2018/8238496 · Cited by 24
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Aivalioti, M. M., Bartholdy, B. A., Pradhan, K., Bhagat, T. D., Zintiridou, A., Jeong, J. J., Thiruthuvanathan, V. J., Pujato, M., Paranjpe, A., Zhang, C., et al. (2022) · Blood Cancer Discovery · doi:10.1158/2643-3230.bcd-21-0226 · Cited by 22
Wang, Z., Li, Z., Wu, D., Tian, Q., Su, S., Cheng, C., Nie, J., Yuan, Y., Wang, Y., & Xu, X. (2023) · The Plant Journal · doi:10.1111/tpj.16153 · Cited by 22
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Braz, C. U., Passamonti, M. M., & Khatib, H. (2024) · Environmental Epigenetics · doi:10.1093/eep/dvad010 · Cited by 19
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Lareau, C. A., Ludwig, L. S., & Sankaran, V. G. (2019) · Blood Advances · doi:10.1182/bloodadvances.2019001196 · Cited by 17
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Korthauer, K., & Irizarry, R. A. (2018) · doi:10.1101/381145 · Cited by 14
Prigozhin, D. M., Sutherland, C. A., Rangavajjhala, S., & Krasileva, K. V. (2025) · Molecular Plant-Microbe Interactions® · doi:10.1094/mpmi-05-24-0047-fi · Cited by 13
Payen, C., Guillot, A., Paillat, L., Fothi, A., Dib, A., Bourreau, J., Schmitt, F., Loufrani, L., Aranyi, T., Henrion, D., et al. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00777-7 · Cited by 12
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Olsen, M. B., Sannes, A.-C., Yang, K., Nielsen, M. B., Einarsen, S. V., Christensen, J. O., Pallesen, S., Bjørås, M., & Gjerstad, J. (2022) · iScience · doi:10.1016/j.isci.2022.104953 · Cited by 9
Khodaeiaminjan, M., Gomes, C., Pagano, A., Kruszka, D., Sulima, P., Przyborowski, J. A., Krajewski, P., & Paiva, J. A. P. (2024) · Physiologia Plantarum · doi:10.1111/ppl.14403 · Cited by 9
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Oksanen, M., Mastropasqua, F., Mazan-Mamczarz, K., Martindale, J. L., Ye, X., Arora, A., Banskota, N., Gorospe, M., & Tammimies, K. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag107 · Cited by 7
Bartlett, T. E., Jia, P., Chandna, S., & Roy, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-03161-7 · Cited by 6
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O’Toole, N., Zhang, T.-Y., Wen, X., Diorio, J., Silveira, P. P., Labonté, B., Nestler, E. J., & Meaney, M. J. (2019) · doi:10.1101/690826 · Cited by 6
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Ge, A. Y., Arab, A., Dai, R., Navickas, A., Fish, L., Garcia, K., Asgharian, H., Goudreau, J., Lee, S., Keenan, K., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-77314-9 · Cited by 4
Cheng, C. C. Y., Cheung, M. F., Lee, A. Y., Wu, Q., Chow, S. H.-C., Ang, J. Y. J., Riquelme Medina, I., Lo, G., Wu, H., Yang, W., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-09154-w · Cited by 3
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Metadata
- Authors
- Krueger, F., & Andrews, S. R.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-04-14
- Volume
- 27
- Issue
- 11
- Pages
- 1571-1572
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2131374955
- Cited by
- 5,297
- References
- 3
- FWCI
- 25.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
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