Meta-analysis is pervasively used to combine multiple genome-wide association studies
(GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort
study. Here, we first demonstrate that heterogeneity (eg, of sample size, phenotyping,
imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary
statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis
summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping …