LAUSR

While thousands of genetic variants have been associated with human traits, identifying the subset of those variants that are causal requires a further 'fine-mapping' step. We review the standard fine-mapping approach, which is computationally fast and requires only summary data, but depends on an assumption of a single causal variant per associated region which is recognised as biologically unrealistic. We discuss different ways that the approach has been built upon to accommodate multiple causal variants in a region, and to incorporate additional layers of functional annotation data. We further review methods for simultaneous fine-mapping of multiple datasets, either exploiting different linkage disequilibrium structures across ancestries, or borrowing information between distinct but related traits. Finally, we look to the future, and the opportunities that will be offered by increasingly accurate maps of causal variants for a multitude of human traits.