MAGMA: Generalized Gene-Set Analysis of GWAS Data

摘要: By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute valuable addition to single-marker analysis. However, although various methods currently exist, they generally suffer from number of issues. Statistical power most is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard detect, the reliance on permutation compute p-values tends make computationally very expensive. To address these issues we have developed MAGMA, novel tool The based multiple regression model, provide better statistical performance. built as separate layer around additional flexibility. This also uses structure allow generalization continuous properties genes simultaneous sets other properties. Simulations an Crohn’s Disease used evaluate performance MAGMA compare it tools. results show that has significantly more than tools both analysis, identifying associated with while maintaining correct type 1 error rate. Moreover, was found be considerably faster well.