Multi-marker Analysis of GenoMic Annotation (MAGMA; de Leeuw et al., 2015) is a method that uses genetic association data to calculate gene-level association scores and gene set enrichment analysis.
To calculate gene-level association scores, we run MAGMA on the bottom-line association results for each trait with its default parameters and a window size of 50kb. We calculate MAGMA associations within each ancestry, as well as at the transethnic level.
We estimate LD using an appropriate subset of samples from the 1000 Genomes Project:
- African 1000G samples for the African American ancestry
- East Asian 1000G samples for the East Asian ancestry
- European 1000G samples for the European ancestry
- Middle/South American 1000G samples for the Hispanic or Latin American ancestry
- South Asian 1000G samples for the South Asian ancestry.
A generally accepted threshold for significance of gene-level MAGMA results is p ≤ 2.5e-6. Note that a MAGMA significant result indicates that the gene is close to a significantly associated variant, but this should not be taken to mean that the gene itself is necessarily causal for the phenotype. If multiple genes are nearby an association, MAGMA assigns low p-values to all of them.
To perform MAGMA pathway analysis, we use default parameters with the C2 (curated gene sets) and C5 (ontology gene sets) collections from the Molecular Signatures Database (MSigDB).