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Updated: Sep 9, 2025

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
SAGA (Simplified Association Genome-wide Analyses): a user-friendly Pipeline to Democratize Genome-Wide Association
Basilio Cieza1, Neetesh Pandey1, Vivek Ruhela1
1Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University. 630 West 168 Street, New York, NY 10032, USA.
Abstract:
Genome-wide association studies (GWAS) have enabled clinicians and researchers to identify genetic variants linked to complex traits and diseases(1-3). However, GWAS still face several challenges, particularly regarding accessibility and reproducibility (4-6). Conducting these analyses often requires substantial bioinformatics expertise for data preprocessing, software installation, and scripting(7-10). We then developed SAGA ("Simplified Association Genome-wide Analyses"), a BASH-based, open-source, fully automated pipeline that integrates three widely adopted tools-PLINK(11), GMMAT(12), and SAIGE(13)-for accessible, robust, and reproducible GWAS. After installation, users simply need to provide genotype and phenotype files in standard formats. The pipeline automates preprocessing, association testing, and visualization, outputting summary statistics, Manhattan plots, and quantile-quantile plots. SAGA enables robust GWAS for users without scripting experience, expanding access to complex genetic analyses.
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