First, we compared the run time and precision of Pascal to those of VEGAS[11], one of the current state-of-the-art gene scoring tools. To this end, we applied both procedures to genome-wide p-values obtained from two large-scale GWAS meta-analyses: The first used about 2.5 million HapMap imputed SNPs[23,24] and the second was based on about 6.4 million SNPs imputed based on a common subset of 1000 Genomes Project (1KG) panel[22,25]. As benchmark we used the results from VEGAS for the former and VEGAS2 (a recent implementation of VEGAS that uses pre-computed LD matrices from 1KG[26]) for the latter. We observed a substantially smaller run time for our method in both cases (Fig 2A): for the HapMap imputed data, VEGAS took 29 hours to compute 18,132 gene scores, while Pascal was considerably faster, needing only about 30 minutes for either statistical test (sum or max) on a single core (Intel Xeon CPU, 2.8GHz). For the 1KG imputed data, Pascal finished the computation in under two hours for either statistic, whereas VEGAS2 took over ten days.
