A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples.

ABSTRACT:

Background

Accurate analysis of whole-gene expression and individual-exon expression is essential to characterize different transcript isoforms and identify alternative splicing events in human genes. One of the omic technologies widely used in many studies on human samples are the exon-specific expression microarray platforms.

Results

Since there are not many validated comparative analyses to identify specific splicing events using data derived from these types of platforms, we have developed an algorithm (called ESLiM) to detect significant changes in exon use, and applied it to a reference dataset of 270 human genes that show alternative expression in different tissues. We compared the results with three other methodological approaches and provided the R source code to be

SUBMITTER: Risueno A 

PROVIDER: S-EPMC4298068 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature