both methods to reduce the likelihood of false-positive results. Coloc is a method that uses a bayesian framework to calculate a probability that 2 traits share a causal variant, whereas TWAS uses prediction models trained on reference QTL data to assess the association between gene expression and disease.11,12,13 The increased size and comprehensiveness of publicly available brain QTL data sets, coupled with advancements in bioinformatic tools, allow for a more thorough investigation of which of the putative genes suggested by GWAS underlie PD risk.
