agriGO is a web-based GO analysis toolkit designed for the agricultural community, built upon the previous GO enrichment tool, EasyGO. It offers enhanced functionalities, including support for 38 agricultural species with 274 data types, flexible user input, and new analysis methods such as Gene Set Enrichment Analysis (GSEA) and Parametric Analysis of Gene Set Enrichment (PAGE). The toolkit includes four tools: SEA (Singular Enrichment Analysis), PAGE, BLAST4ID (Transfer IDs by BLAST), and SEACOMPARE (Cross Comparison of SEA), enabling users to compare different datasets and visualize results. agriGO also serves as a GO data repository with search and download functions, accessible at http://bioinfo.cau.edu.cn/agriGO/. The system architecture and interface were redesigned to improve performance and accessibility. agriGO supports a wide range of organisms and gene identifiers, including those from publicly available databases and newly sequenced species. It provides comprehensive annotations, including gene descriptions and protein domain annotations, which are searchable and downloadable. The tool uses advanced statistical methods, such as the Benjamini–Yekutieli method, for multiple testing correction, and offers customizable graphical outputs, including hierarchical tree graphs and flash bar charts, to facilitate biological interpretation. agriGO allows users to perform cross-comparisons of results from different datasets, which is particularly useful for time-course experiments. It also includes a BLAST4ID tool for ID mapping and connecting unidentified IDs to analysis tools within agriGO. The web interface is user-friendly, with an interactive help system and flexible input requirements. The tool is implemented on a LAMP platform and regularly updated to ensure the latest data availability. agriGO provides a comprehensive solution for GO-based functional analysis in agricultural research, offering improved functionalities compared to EasyGO. It enables researchers to extract biological insights from high-throughput experiments in an efficient and systematic manner. The tool is freely accessible and supports a wide range of organisms, making it a valuable resource for the agricultural community.agriGO is a web-based GO analysis toolkit designed for the agricultural community, built upon the previous GO enrichment tool, EasyGO. It offers enhanced functionalities, including support for 38 agricultural species with 274 data types, flexible user input, and new analysis methods such as Gene Set Enrichment Analysis (GSEA) and Parametric Analysis of Gene Set Enrichment (PAGE). The toolkit includes four tools: SEA (Singular Enrichment Analysis), PAGE, BLAST4ID (Transfer IDs by BLAST), and SEACOMPARE (Cross Comparison of SEA), enabling users to compare different datasets and visualize results. agriGO also serves as a GO data repository with search and download functions, accessible at http://bioinfo.cau.edu.cn/agriGO/. The system architecture and interface were redesigned to improve performance and accessibility. agriGO supports a wide range of organisms and gene identifiers, including those from publicly available databases and newly sequenced species. It provides comprehensive annotations, including gene descriptions and protein domain annotations, which are searchable and downloadable. The tool uses advanced statistical methods, such as the Benjamini–Yekutieli method, for multiple testing correction, and offers customizable graphical outputs, including hierarchical tree graphs and flash bar charts, to facilitate biological interpretation. agriGO allows users to perform cross-comparisons of results from different datasets, which is particularly useful for time-course experiments. It also includes a BLAST4ID tool for ID mapping and connecting unidentified IDs to analysis tools within agriGO. The web interface is user-friendly, with an interactive help system and flexible input requirements. The tool is implemented on a LAMP platform and regularly updated to ensure the latest data availability. agriGO provides a comprehensive solution for GO-based functional analysis in agricultural research, offering improved functionalities compared to EasyGO. It enables researchers to extract biological insights from high-throughput experiments in an efficient and systematic manner. The tool is freely accessible and supports a wide range of organisms, making it a valuable resource for the agricultural community.