mtag

mtag jointly analyzes multiple sets of genome-wide association study (GWAS) summary statistics to increase the number of identified associated loci and improve association statistics for downstream analyses.

Key Features:

• Multi-trait analysis: Performs joint analysis of summary statistics from GWAS of different traits, possibly from overlapping samples.
• Meta-analysis capability: Can also be used to meta-analyze GWAS results.
• Increased locus discovery: Increases the number of genome-wide significant loci identified compared to single-trait GWAS.
• Enhanced polygenic prediction: Increases the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

Scientific Applications:

• Psychiatric and behavioral trait analysis: Applied to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538).
• Bioinformatics analysis enhancement: Association statistics from MTAG yield more informative bioinformatics analyses.
• Polygenic score construction: Improves the predictive utility of polygenic scores for complex traits.

Methodology:

The method uses a statistical framework for joint analysis of GWAS summary statistics from multiple traits, accounting for sample overlap between studies.