可视化
口译(哲学)
计算机科学
数据可视化
数据科学
数据挖掘
程序设计语言
作者
Xiaofan Lu,Kailai Li,Zongcheng Li,Anqi Lin,Long Zhao,Rongfang Shen,Zhou-Geng Xu,Jianing Gao,Dekang Lv,Yasi Zhang,Taojun Ye,Junyi Shen,Yijing Chen,Hui Huang,Zhaodong Hao,Dongqiang Zeng,Haitao Wang,Shipeng Guo,Wen Wang,Yi Xiong
摘要
ABSTRACT Biomedical research data visualization faces several challenges, including insufficient expertise and fragmented methodologies, which severely limit research efficiency and result quality. FigureYa is a standardized visualization framework composed of 317 modular R/python scripts, rather than a standalone software or desktop application. It covers key domains such as expression profiling, immune analysis, survival analysis, and single‐cell data visualization. Based on the concept of “replace data and use,” FigureYa significantly lowers the technical threshold, allowing researchers to generate high‐quality charts without requiring an extensive programming background. Compared to generic online R code snippets, FigureYa offers rigorously developed, thoroughly validated, and biologically contextualized visualization modules originally written by the author team. Each script includes version‐matched environments, example datasets, and detailed annotations, providing clear advantages in automation, reproducibility, and scientific professionalism, thereby providing a standardized visualization solution for complex biomedical data. This innovative tool optimizes research time allocation, promotes interdisciplinary collaboration, accelerates scientific discovery and clinical translation, and provides robust data visualization support for biomedical research.
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