Often investigators need to calculate power to demonstrate feasibility of proposed genetic studies for grant proposals or simply to aid in their own study planning. Frequently, power can be easily calculated using a closed form formula. However, in some situations such formulae for calculating power have not been derived and derivation on demand may be difficult if not impossible. In these situations investigators typically perform simulations specific to the study. Yet such simulations can be computationally extensive and take weeks to months depending on the circumstances. Here, we provide a simple method to rapidly estimate power when one has power estimates available for corresponding situations that differ from the situation of interest only in sample size and/or alpha (type I error) level desired. We show by application to multiple published results from the genomics field that these methods are generally very accurate and applicable to a broad range of genomic studies.