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.

Availability and implementation: http://www.well.ox.ac.uk/~rivas/mamba/. R-sources and data examples http://www.iki.fi/mpirinen/

Contact: matti.pirinen@helsinki.fi or rivas@well.ox.ac.uk

Supplementary information: Supplementary data are available at Bioinformatics online.