Allele Specific Expression Quality Control Fills Critical Gap in Transcriptome Assisted Rare Variant Interpretation.

ABSTRACT: Allele-specific expression (ASE) captures the functional impact of genetic variation on transcription, offering a high-resolution view of cis-regulatory effects, but its quality can be diminished by technical, biological, and analysis artifacts. We introduce aseQC, a statistical framework that quantifies sample-level ASE quality in terms of the overall expected extra-binomial variation to exclude uncharacteristically noisy samples in a cohort to improve robustness of downstream analyses. Applying aseQC to a dataset of rare mendelian muscular disorders, successfully identified previously annotated low-quality cases demonstrating clinical genomic utility. When applied to 15,253 samples in extensively quality controlled GTEx project data, aseQC uncovered 563 low-quality samples that exhibit e

SUBMITTER: Ganapathy KR 

PROVIDER: S-EPMC12157414 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature