Jul 17, 2014

Assessing allele specific expression across multiple tissues from RNA-seq read data

BioRxiv : the Preprint Server for Biology
Matti PirinenManuel A Rivas

Abstract

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 project (GTEx) 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. Availability: MAMBA software: [http://birch.well.ox.ac.uk/∼rivas/mamba/][1] R source code and data examples: <http://www.iki.fi/mpirinen/> Contact: matti.pirinen{at}helsinki.fi rivas{at}well.ox.ac.uk [1]: http://birch.well.ox.ac.uk/%E2%88%BCrivas/mamba/

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Mentioned in this Paper

Computer Software
Study
Projections and Predictions
Mamba
Birch antigen
Sequence Determinations, RNA
Betula Genus
Simulation
Statistical Technique
Analysis

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