Wang Xin, Xin Beibei, Guo Maozu, Yu Guoxian, Wang Jun
School of Software, Shandong University, Jinan 250101, China.
Joint SDU-NTU Centre for Artificial Intelligence Research, Shandong University, Jinan 250101, China.
Fundam Res. 2024 Mar 22;4(4):761-769. doi: 10.1016/j.fmre.2024.03.005. eCollection 2024 Jul.
The genome-wide association study (GWAS) aims to detect associations between individual single nucleotide polymorphisms (SNPs) or SNP interactions and phenotypes to decipher the genetic mechanism. Existing GWAS analysis tools have different focuses and advantages, but suffer a series of tedious and heterogeneous configurations for computation. It is inconvenient for researchers to simply choose and apply these tools, statistically and biologically analyze their results for different usages. To address these issues, we develop a user friendly web pipeline GWASTool for detecting associations, which includes simulation data generation, associated loci detection, result visualization, analysis and comparison. GWASTool provides a unified and plugin-able framework to encapsulate the heterogeneity of GWAS algorithms, simplifies the analysis steps and energizes GWAS tasks. GWASTool is implemented in Java and is freely available for public use at http://www.sdu-idea.cn/GWASTool. The website hosts a comprehensive collection of resources, including a user manual, description of integrated algorithms, data examples and standalone version for download.
全基因组关联研究(GWAS)旨在检测个体单核苷酸多态性(SNP)或SNP相互作用与表型之间的关联,以破译遗传机制。现有的GWAS分析工具各有不同的侧重点和优势,但在计算方面存在一系列繁琐且异构的配置。研究人员难以简单地选择和应用这些工具,并针对不同用途对其结果进行统计和生物学分析。为了解决这些问题,我们开发了一个用户友好的网络管道GWASTool用于检测关联,它包括模拟数据生成、关联位点检测、结果可视化、分析和比较。GWASTool提供了一个统一且可插件的框架来封装GWAS算法的异构性,简化了分析步骤并为GWAS任务注入活力。GWASTool用Java实现,可在http://www.sdu-idea.cn/GWASTool上免费供公众使用。该网站拥有全面的资源集合,包括用户手册、集成算法描述、数据示例和可供下载的独立版本。