PT  - JOURNAL ARTICLE
AU  - Matti Pirinen
AU  - Tuuli Lappalainen
AU  - Noah A. Zaitlen
AU  - GTEx Consortium
AU  - Emmanouil T. Dermitzakis
AU  - Peter Donnelly
AU  - Mark I. McCarthy
AU  - Manuel A. Rivas
TI  - Assessing allele specific expression across multiple tissues from RNA-seq read data
AID  - 10.1101/007211
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 007211
4099  - http://biorxiv.org/content/early/2014/07/17/007211.short
4100  - http://biorxiv.org/content/early/2014/07/17/007211.full
AB  - 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/ R source code and data examples: http://www.iki.fi/mpirinen/Contact: matti.pirinen{at}helsinki.firivas{at}well.ox.ac.uk