Power calculator for detecting allelic imbalance using hierarchical Bayesian model

BMC Research Notes

Luis G. León-Novelo¹  Fabio Marroni²  Lauren M. McIntyre³  Sergey V. Nuzhdin⁴  Katrina Sherbina⁵ 

[1] Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston-School of Public Health, 77030, Houston, TX, USA;Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università di Udine, 33100, Udine, Italy;Genetics Institute and Department of Molecular Genetics and Microbiology, University of Florida, 32603, Gainesville, FL, USA;Molecular and Computational Biology Section, University of Southern California, 90046, Los Angeles, CA, USA;Quantitative and Computational Biology Section, University of Southern California, 90046, Los Angeles, CA, USA;

关键词: Allelic imbalance;    Type I error;    Power;    Simulation;    Allele specific reads;    Biological replicates;   

DOI  :  10.1186/s13104-021-05851-x

来源: Springer

【 摘 要 】

ObjectiveAllelic 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?ResultsWe 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.

【 授权许可】

CC BY