Author:
Cao Tianze,Li Qian,Huang Yuexia,Li Anshui
Abstract
Abstract
Background
The visual sequence logo has been a hot area in the development of bioinformatics tools. ggseqlogo written in R language has been the most popular API since it was published. With the popularity of artificial intelligence and deep learning, Python is currently the most popular programming language. The programming language used by bioinformaticians began to shift to Python. Providing APIs in Python that are similar to those in R can reduce the learning cost of relearning a programming language. And compared to ggplot2 in R, drawing framework is not as easy to use in Python. The appearance of plotnine (ggplot2 in Python version) makes it possible to unify the programming methods of bioinformatics visualization tools between R and Python.
Results
Here, we introduce plotnineSeqSuite, a new plotnine-based Python package provides a ggseqlogo-like API for programmatic drawing of sequence logos, sequence alignment diagrams and sequence histograms. To be more precise, it supports custom letters, color themes, and fonts. Moreover, the class for drawing layers is based on object-oriented design so that users can easily encapsulate and extend it.
Conclusions
plotnineSeqSuite is the first ggplot2-style package to implement visualization of sequence -related graphs in Python. It enhances the uniformity of programmatic plotting between R and Python. Compared with tools appeared already, the categories supported by plotnineSeqSuite are much more complete. The source code of plotnineSeqSuite can be obtained on GitHub (https://github.com/caotianze/plotnineseqsuite) and PyPI (https://pypi.org/project/plotnineseqsuite), and the documentation homepage is freely available on GitHub at (https://caotianze.github.io/plotnineseqsuite/).
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference43 articles.
1. Schneider TD, Stephens RM. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res. 1990;18(20):6097–100.
2. Colaert N, Helsens K, Martens L, Vandekerckhove J, Gevaert K. Improved visualization of protein consensus sequences by iceLogo. Nat Methods. 2009;6(11):786–7.
3. Gorodkin J, Heyer LJ, Brunak S, Stormo GD. Displaying the information contents of structural RNA alignments: the structure logos. Comput Appl Biosci. 1997;13(6):583–6.
4. Maddelein D, Colaert N, Buchanan I, Hulstaert N, Gevaert K, Martens L. The iceLogo web server and SOAP service for determining protein consensus sequences. Nucleic Acids Res. 2015;43(W1):W543–546.
5. Menzel P, Seemann SE, Gorodkin J. RILogo: visualizing RNA-RNA interactions. Bioinformatics. 2012;28(19):2523–6.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献