Testcrosses are an efficient strategy for identifying <i>cis</i>-regulatory variation: Bayesian analysis of allele-specific expression (BayesASE)

Abstract Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects natural population? Are all same? distinct? The approach described applies to any technology generating allele-specific sequence counts, for example chromatin accessibility can be applied generally including comparisons between tissues or environments same genotype. Tests effect performed by crossing individuals comparing expression directly F1. However, scheme that compares pairwise prohibitive cost more than handful as number crosses at least (n2-n)/2 where n alleles. We show here testcross design followed hypothesis test AI testcrosses used infer differences nontester alleles, allowing compared with crosses. Using mouse data set both direct have been performed, we predicted validated levels over 90% parent-of-origin present 60%−80% overall. Power considerations testcross, similar those reciprocal cross. In applications, testing involves several complex bioinformatics steps. BayesASE complete pipeline incorporates state-of-the-art error reduction techniques flexible Bayesian estimating formally conditions. modular structure has packaged Galaxy, made available Nextflow collection scripts SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE).