variants (e.g. 3 or 6); more recent studies have shown that further speed-ups can be achieved through matrix factorizations48 or stochastic search49. Methods that model multiple causal variants generally improve the accuracy (and calibration) of credible sets at loci with multiple causal variants46–50, with very limited decreases in accuracy at loci with only a single causal variant46–52. A less accurate alternative is to use conditional association analysis to detect multiple signals of associations7,53,54, followed by estimation of posterior probabilities of causality under a single causal variant assumption for each independent signal. In this case, special care is required in specifying the boundaries of each independent signal and the threshold for the conditional test.
