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MOTIVATION: RNA sequencing enables allele-specific expression (ASE) studies that complement standard genotype expression studies for common variants and, importantly, also allow measuring the regulatory impact of rare variants. The Genotype-Tissue Expression (GTEx) project is collecting RNA-seq data on multiple tissues of a same set of individuals and novel methods are required for the analysis of these data. RESULTS: We present a statistical method to compare different patterns of ASE across tissues and to classify genetic variants according to their impact on the tissue-wide expression profile. We focus on strong ASE effects that we are expecting to see for protein-truncating variants, but our method can also be adjusted for other types of ASE effects. We illustrate the method with a real data example on a tissue-wide expression profile of a variant causal for lipoid proteinosis, and with a simulation study to assess our method more generally.

Original publication

DOI

10.1093/bioinformatics/btv074

Type

Journal article

Journal

Bioinformatics

Publication Date

01/08/2015

Volume

31

Pages

2497 - 2504

Keywords

Alleles, Extracellular Matrix Proteins, High-Throughput Nucleotide Sequencing, Humans, Lipoid Proteinosis of Urbach and Wiethe, Organ Specificity, Polymorphism, Single Nucleotide, Protein Isoforms, RNA