Power calculator for detecting allelic imbalance using hierarchical Bayesian model

BMC Res Notes. 2021 Nov 27;14(1):436. doi: 10.1186/s13104-021-05851-x.

Abstract

Objective: Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates?

Results: We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions.

Keywords: Allele specific reads; Allelic imbalance; Biological replicates; Power; Simulation; Type I error.

MeSH terms

  • Alleles
  • Allelic Imbalance*
  • Bayes Theorem
  • Computer Simulation
  • Humans