AbstractSummaryGenome-wide association studies (GWASs) have identified numerous genetic variants associated with complex disease risk; however, most of these associations are non-coding, complicating identifying their proximal target gene. Transcriptome-wide association studies (TWASs) have been proposed to mitigate this gap by integrating expression quantitative trait loci (eQTL) data with GWAS data. Numerous methodological advancements have been made for TWAS, yet each approach requiresad hocsimulations to demonstrate feasibility. Here, we presenttwas_sim, a computationally scalable and easily extendable tool for simplified performance evaluation and power analysis for TWAS methods.Availability and implementationSoftware and documentation are available athttps://github.com/mancusolab/twas_sim.