DataColor: unveiling biological data relationships through distinctive color mapping

文献类型： 外文期刊

第一作者： He, Shuang

作者： He, Shuang;Zhang, Junyu;Yang, Shuting;Wang, Wenquan;Chen, Fei;He, Shuang;Zhang, Junyu;Yang, Shuting;Wang, Wenquan;Chen, Fei;Dong, Wei;Chen, Junhao;Lin, Weiwei;Xu, Dong;Zhou, Yuhan;Miao, Benben

作者机构：

期刊名称：HORTICULTURE RESEARCH （ 影响因子：8.7； 五年影响因子：9.0 ）

ISSN： 2662-6810

年卷期： 2024 年 11 卷 2 期

页码：

收录情况： SCI

摘要： 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: https://github.com/frankgenome/DataColor.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序