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Ornamental and Medicinal Plants, 2026, 9(1-4): 1-21
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Article

Fetching GWAS (Genome-Wide Association Study) data via AI: A web tool to synthesize genotype, phenotype, and summary statistics

WenJun Zhang1, Yanhong Qi2
1School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; International Academy of Ecology and Environmental Sciences, Hong Kong
2Libraries of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China

Received 1 November 2025;Accepted 16 November 2025;Published online 1 December 2025;Published 1 September 2026
IAEES

Abstract
A GWAS (Genome-Wide Association Study) data fetcher via AI was developed in present study. It is a web tool that generates realistic synthetic GWAS data based on user inputs via AI APIs (OpenAI, DeepSeek, or Google Gemini). It outputs three data components: (1) summary statistics: an array of SNP records (CHR, SNP, BP, A1, A2, FRQ_A1, BETA, SE, P, N, INFO), (2) phenotype data: an array of 10 individual records (FID, IID, PHE, SEX, AGE, PC1, PC2, BATCH), and (3) metadata: a descriptive string containing genotyping platform, QC protocols, genome build, and population notes. By leveraging AI to generate realistic data, users can practice analysis without accessing restricted genetic databases, test analysis pipelines safely, learn GWAS data structure and format, and develop and validate bioinformatics tools.

Keywords GWAS (Genome-Wide Association Study);data fetcher;Artificial Intelligence (AI);Large Language Model (LLM);JavaScript/HTML.


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