DataColor: unveiling biological data relationships through distinctive color mapping

Abstract

In the era of rapid advancements in high-throughput omics technologies, the visualization of diverse data types with varying orders of magnitude presents a pressing challenge. To bridge this gap, we introduce DataColor, an all-encompassing software solution meticulously crafted to address this challenge. Our aim is to empower users with the ability to handle a wide array of data types through an assortment of tools, while simultaneously streamlining parameter selection for rapid insights and detailed enhancements. DataColor stands as a robust toolkit, encompassing 23 distinct tools coupled with over 600 parameters. The defining characteristic of this toolkit is its adept utilization of the color spectrum, allowing for the representation of data spanning diverse types and magnitudes. Through the integration of advanced algorithms encompassing data clustering, normalization, squarified layouts, and customizable parameters, DataColor unveils an abundance of insights that lay hidden within the intricate relationships embedded in the data. Whether you find yourself navigating the analysis of expansive datasets or embarking on the quest to visualize intricate patterns, DataColor stands as the comprehensive and potent solution. We extend the availability of DataColor to all users at no cost, accessible through the following link:

Acknowledgements

This work was supported by the National Natural Science Foundation of China (32472614), National Natural Science Foundation of China-CG joint foundation (3181101517), Hainan Province Science and Technology Special Fund (ZDYF2023XDNY050). Authors thank the anonymous reviewers for their invaluable comments and suggestions.

Author contributions

Fei Chen and Wenquan Wang designed and led this project. Shuang He and Junhao Chen wrote the codes. Shuang He, Wei Dong, Junyu Zhang, Weiwei Lin, Shuting Yang, Dong Xu, Yuhan Zhou, and Benben Miao participated in software improvement. Shuang He and Fei Chen wrote the draft manuscript. W.W., Shuang He, and Fei Chen discussed and revised the manuscript. All authors have read and agreed the final manuscript.

Data availability

The software, user documents, and test data are available at GitHub (https://github.com/frankgenome/DataColor), gitee (https://gitee.com/heshuang-linda/DataColor), and figshare (https://figshare.com/account/home#/projects/169160).

Conflict of interest statement

The authors declare that they have no conflict of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

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