Chamaeleo is currently the only collection library that focuses on adapting multiple well-established coding schemes for DNA storage. It provides a tool for researchers to study various coding schemes and apply them in practice. Chamaeleo adheres to the concept of high aggregation and low coupling for software design which will enhance the performance efficiency. Here, we describe the working pipeline of Chamaeleo, and demonstrate its advantages over the implementation of existing single coding schemes. The source code is available at <https://github.com/ntpz870817/Chamaeleo>, it can be also installed by the command of pip.exe, “pip install chamaeleo”. Alternatively, the wheel file can be downloaded at <https://pypi.org/project/Chamaeleo/>. Detailed documentation is available at <https://chamaeleo.readthedocs.io/en/latest/>. Author Summary DNA is now considered to be a promising candidate media for future digital information storage in order to tackle the global issue of data explosion. Transcoding between binary digital data and quanternary DNA information is one of the most important steps in the whole process of DNA digital storage. Although several coding schemes have been reported, researchers are still investigating better strategies. Moreover, the scripts of these coding schemes use different programming languages, software architectures and optimization contents. Therefore, we here introduce Chamaeleo, a library in which several classical coding schemes are collected, to reconstruct and optimize them. One of the key features of this tool is that we modulize the functions and make it feasible for more customized way of usage. Meanwhile, developers can also incorporate their new algorithms according to the framework expediently. Based on the benchmark tests we conducted, Chamaeleo shows better flexibility and expandability compared to original packages and we hope that it will help the further study and applications in DNA digital storage.
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