Improved Identification of Large-effect Rare Genetic Variants using Haplotype Aggregated Allele-specific Expression Data.

ABSTRACT: Allele-specific expression (ASE) outlier detection is a powerful tool for identifying genes affected by large effect rare genetic regulatory variants but suffers from data sparsity and noisy signal in low-count genes. Genome phasing can be utilized to aggregate ASE signal along haplotypes to alleviate both sparsity and noise. Yet statistical tools for utilizing haplotype-level ASE data for rare variant interpretation are lacking. Here, we present ANEVA-h, to quantify the amount of genetic variation in gene expression from haplotype-level ASE data in a population, enabling more accurate and comprehensive detection of regulatory effects. We apply ANEVA-h to GTEx project data, along with a compatible dosage outlier test, to show an over 2-fold increase in the number of testable genes, reducti

SUBMITTER: Ganapathy KR 

PROVIDER: S-EPMC12723776 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature