agriGO
agriGO performs gene ontology (GO) analyses tailored for agricultural research.
Key Features:
- Expanded Organism and Gene Identifier Support: Supports 38 agricultural species across 274 data types for broad coverage of agricultural gene sets.
- Flexible User Input: Accepts user-defined reference datasets and annotations for customized analyses.
- Gene Set Enrichment Strategies: Incorporates Gene Set Enrichment Analysis (GSEA) alongside enrichment approaches for functional interpretation.
- Integrated Analysis Tools: Provides SEA (Singular Enrichment Analysis), PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (transfer of gene identifiers by BLAST), and SEACOMPARE (cross comparison of SEA).
- Cross-Comparison and Visualization: Enables comparative analysis across multiple datasets and visualization of comparative enrichment results.
- GO Data Repository: Serves as a repository for GO data with search and download functionality.
Scientific Applications:
- Functional Annotation: Assigns and interprets GO terms for gene sets derived from high-throughput experiments.
- Enrichment Analysis: Detects over-represented GO categories using SEA, PAGE, and GSEA methodologies.
- Comparative Genomics: Facilitates cross-species and cross-dataset comparisons of GO enrichment, including ID transfer via BLAST4ID.
- Agricultural and Plant Research: Supports studies in plant biology, crop improvement, and sustainable agriculture by enabling cross-species functional exploration.
Methodology:
Performs GO analyses using SEA, PAGE, and GSEA; transfers gene identifiers via BLAST4ID; performs cross-dataset comparison with SEACOMPARE; accepts user-defined reference datasets and annotations and provides GO data search and download.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- PHP
- Added:
- 3/25/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Du Z, Zhou X, Ling Y, Zhang Z, Su Z. agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Research. 2010;38(suppl_2):W64-W70. doi:10.1093/nar/gkq310. PMID:20435677. PMCID:PMC2896167.
Documentation
User manual
http://bioinfo.cau.edu.cn/agriGO/manual.php