SAGA (Simplified Association Genome-wide Analyses): a user-friendly Pipeline to Democratize Genome-Wide Association Studies

Abstract excerpt

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 de...

Topics

Open a Topic to create a Post that cites this publication.

• Data Interpretation, Statistical
• Genome-Wide Association Study
• Guidelines as Topic
• Multifactorial Inheritance
• Phenotype
• Polymorphism, Single Nucleotide
• Quality Control
• Risk Assessment

Identifiers and source

Literature Corpus work

0400ca7b-2c91-5f79-818d-9689fbf192ab

DOI

10.1101/2025.08.25.672146