Gene Ontology Web Tool

Purpose & User Intent:\nThe tool solves the problem of identifying overrepresented GO terms in a user-provided gene set, with background-aware statistics and namespace organization. It targets researchers in functional genomics, bioinformatics, and systems biology who need interpretable functional annotations from experimental data. It is applicable after generating a gene list from RNA-seq, proteomics, or genetic studies, to reveal enriched Biological Process, Molecular Function, and Cellular Component terms.\n\nCore Logic & Features:\nRequired features include input of a gene list, organism mapping, GO associations, an enrichment calculation using a hypergeometric test, and multiple testing correction with structured outputs that include GO_ID, term_name, namespace, p_value, adjusted_p_value, and the list of contributing genes. Outputs are exportable in CSV/JSON. Optional features cover custom background selection, namespace filtering, minimum gene count per term, and alternative correction methods. The system emphasizes transparent statistics, reproducible results, and per-term gene lists to facilitate reporting.\n\nInputs & Outputs:\nInputs encompass gene_list, organism, optional background_set, p_value_cutoff, min_gene_count, and enrichment_method. Outputs are enriched_terms with per-term details and gene lists, formatted for downstream analysis. p-values are provided in scientific or decimal notation with consistent precision.\n\nAlgorithms & Calculations:\nThe core calculation employs the hypergeometric distribution to evaluate enrichment, followed by Benjamini–Hochberg false discovery rate correction. GO mappings derive from organism-specific annotations. Results are namespace-separated (BP, MF, CC) and ranked by adjusted p-value, with clear per-term gene associations.\n\nError & Edge Cases:\nUnmapped IDs or unavailable organism mappings may yield empty results or warnings in logs. If the background is smaller than the input set, or no term passes the cutoff after adjustment, an empty result is returned with guidance on reconfiguration.\n\nIndustry/Region & Localization:\nGO usage is global and relies on standard ontologies; supports common model organisms and standard gene identifiers, enabling cross-study comparisons and reproducibility.\n\nAssumptions & Exclusions:\nAssumes standard gene identifiers; does not perform pathway-level analyses beyond GO, nor provides UI-specific guidance.