MSS

MSS detects disease-associated genomic segments from genome-wide association study (GWAS) data by applying a two-stage maximal segmental score procedure that uses region-specific empirical P-values combined via Fisher's method for analysis of high-density genotyping arrays and next-generation sequencing.

Key Features:

• Two-Stage Maximal Segmental Score Procedure: Employs a two-stage maximal segmental score procedure that uses region-specific empirical P-values to identify genomic segments likely harboring disease-related genes.
• Scoring System Based on Fisher's Method: Integrates locus-specific significance levels into region-specific scores by combining P-values with Fisher's method.
• Increased Power and Efficiency: Demonstrates increased power to detect genetic associations in simulations while maintaining a type I error rate at 5%.
• Application in Disease Research: Has been applied to case-control datasets, including Parkinson's disease, to replicate published associations.

Scientific Applications:

• Disease Genetics Research: Facilitates identification of susceptibility genes in common disease genetics and addresses unexplained heritability.
• High-Density Genotyping and Next-Generation Sequencing: Scales to screen over 5 million genetic markers from high-density genotyping arrays and next-generation sequencing datasets.

Methodology:

Calculate region-specific empirical P-values, combine P-values into region-specific scores using Fisher's method, and apply a two-stage maximal segmental score procedure to identify significant genomic segments.