Computational detection of alternative exon usage.

ABSTRACT:

Background

With the advent of the GeneChip Exon Arrays, it is now possible to extract "exon-level" expression estimates, allowing for detection of alternative splicing events, one of the primary mechanisms of transcript diversity. In the context of (1) a complex trait use case and (2) a human cerebellum vs. heart comparison on previously validated data, we present a transcript-based statistical model and validation framework to allow detection of alternative exon usage (AEU) between different groups. To illustrate the approach, we detect and confirm differences in exon usage in the two of the most widely studied mouse genetic models (the C57BL/6J and DBA/2J inbred strains) and in a human dataset.

Results

We developed a computational framework that consists of probe level ann

SUBMITTER: Laderas TG 

PROVIDER: S-EPMC3097375 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature