MUGBAS

MUGBAS computes gene-based association P-values from single-marker GWAS results and genotype data across model and non-model species to enable gene-level association analysis of functional units containing multiple molecular markers.

Key Features:

• Species Independence: Applicable to model and non-model organisms without species-specific adaptations.
• Annotation-Independent: Operates without relying on predefined annotations, allowing use with variable annotation quality.
• Integration with Single Marker GWAS Results: Utilizes single-marker GWAS results together with genotype data to estimate gene-based P-values.
• Highly Parallelized and Efficient: Implements parallel computation to accelerate gene-level P-value calculations.
• Scalability for High-Density Marker Studies: Designed to handle large-scale, high-density marker datasets typical of modern GWAS.

Scientific Applications:

• Gene discovery for phenotypic traits: Identifies genes associated with phenotypic variation by aggregating marker-level associations.
• Investigation of complex genetic architectures: Evaluates the collective impact of multiple markers within genes to study polygenic signals.
• Comparative genomics and evolutionary studies: Enables cross-species gene-based association analyses to support comparative and evolutionary investigations.

Methodology:

Calculates gene P-values from constituent marker associations by incorporating single-marker GWAS results, genotype data, and gene annotations, and performs these computations using a parallelized architecture.