ImageGP 2 for enhanced data visualization and reproducible analysis in biomedical research
Tong Chen, Tong Chen, Yongxin Liu, Tao Chen, Tao Chen, Mei Yang, Siqing Fan, Minglei Shi, Buqing Wei, Huijiao Lv, Wandi Cao, Chongmin Wang, Jianzhou Cui, Jiwen Zhao, Yilai Han, Jiao Xi, Ziqiang Zheng, Luqi Huang
Abstract
ImageGP is an extensively utilized, open-access platform for online data visualization and analysis. Over the past 7 years, it has catered to more than 700,000 usages globally, garnering substantial user feedback. The updated version, ImageGP 2 (available at https://www.bic.ac.cn/BIC), introduces a redesigned interface leveraging cutting-edge web technologies to enhance functionality and user interaction. Key enhancements include the following: (i) Addition of modules for data format transformation, facilitating operations such as matrix merging, subsetting, and transformation between long and wide formats. (ii) Streamlined workflows with features like preparameter selection data validation and grouping of parameters with similar attributes. (iii) Expanded repertoire of visualization functions and analysis tools, including Weighted Gene Co-Expression Network Analysis, differential gene expression analysis, and FASTA sequence processing. (iv) Personalized user space for uploading large data sets, tracking analysis history, and sharing reproducible analysis data, scripts, and results. (v) Enhanced user support through a simplified error debugging feature accessible with a single click. (vi) Introduction of an R package, ImageGP, enabling local data visualization and analysis. These updates position ImageGP 2 as a versatile tool serving both wet-lab and dry-lab researchers with expanded capabilities.