Genome-wide association studies (GWAS) have enabled clinicians and researchers to identify genetic variants linked to complex traits and diseases(1). However, conducting GWAS remains technically challenging without bioinformatics expertise due to required data preprocessing, software installation, and analysis scripting (2,3). SAGA is a BASH-based, open-source, fully automated pipeline that integrates three widely adopted tools -PLINK, GMMAT and SAIGE- for accessible, robust, and reproducible GWAS. After installation, users only provide standard genotype and phenotype files. The pipeline automates preprocessing, association testing, and visualization, outputting summary statistics, Manhattan plots, and quantile-quantile plot. SAGA enables robust GWAS for users with no scripting experience, expanding access to complex genetic analyses.
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Cieza et al. (2025) studied this question.
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