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ggseqlogo: a versatile R package for drawing sequence logos
Abstract
Summary: Sequence logos have become a crucial visualization method for studying underlying sequence patterns in the genome. Despite this, there remains a scarcity of software packages that provide the versatility often required for such visualizations. ggseqlogo is an R package built on the ggplot2 package that aims to address this issue. ggseqlogo offers native illustration of publication-ready DNA, RNA and protein sequence logos in a highly customizable fashion with features including multi-logo plots, qualitative and quantitative colour schemes, annotation of logos and integration with other plots. The package is intuitive to use and seamlessly integrates into R analysis pipelines. Availability and implementation: ggseqlogo is released under the GNU licence and is freely available via CRAN-The Comprehensive R Archive Network https://cran.r-project.org/web/packages/ggseqlogo. A detailed tutorial can be found at https://omarwagih.github.io/ggseqlogo.
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ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
The Genetics of Transcription Factor DNA Binding Variation
Deplancke, B., Alpern, D., & Gardeux, V. (2016) · Cell · doi:10.1016/j.cell.2016.07.012 · Cited by 390
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Huang, H., Wang, C., Rubelt, F., Scriba, T. J., & Davis, M. M. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0505-4 · Cited by 484
Mason, D. M., Friedensohn, S., Weber, C. R., Jordi, C., Wagner, B., Meng, S. M., Ehling, R. A., Bonati, L., Dahinden, J., Gainza, P., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00699-9 · Cited by 308
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Durrant, M. G., Perry, N. T., Pai, J. J., Jangid, A. R., Athukoralage, J. S., Hiraizumi, M., McSpedon, J. P., Pawluk, A., Nishimasu, H., Konermann, S., et al. (2024) · Nature · doi:10.1038/s41586-024-07552-4 · Cited by 163
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Li, D., Yang, J., Huang, X., Zhou, H., & Wang, J. (2022) · Science Advances · doi:10.1126/sciadv.abm0478 · Cited by 28
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Sun, L., Liu, Y., Guo, X., Cui, T., Wu, C., Tao, J., Cheng, C., Chu, Q., Ji, C., Li, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49573-7 · Cited by 18
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Jabeen, A., Oakeshott, J. G., Lee, S. F., Ranganathan, S., & Taylor, P. W. (2024) · Scientific Reports · doi:10.1038/s41598-024-80094-x · Cited by 11
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Kundnani, D. L., Yang, T., Gombolay, A. L., Mukherjee, K., Newnam, G., Meers, C., Verma, I., Chhatlani, K., Mehta, Z. H., Mouawad, C., et al. (2024) · iScience · doi:10.1016/j.isci.2024.110012 · Cited by 6
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Ross, P., Hilton, H. G., Lodwick, J., Slezak, T., Guethlein, L. A., McMurtrey, C. P., Han, A. S., Nielsen, M., Yong, D., Dulberger, C. L., et al. (2025) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.110542 · Cited by 1
(2026) · doi:10.1042/bcj20250297
(2024) · doi:10.1101/2024.10.03.616434
Metadata
- Authors
- Wagih, O.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-07-20
- Volume
- 33
- Issue
- 22
- Pages
- 3645-3647
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2737196618
- Cited by
- 929
- References
- 2
- FWCI
- 17.86
- Type
- journal article
- Language
- en
- Open access
- closed
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