FIRMA: a method for detection of alternative splicing from exon array data

Abstract

Motivation: Analyses of EST data show that alternative splicing is much more widespread than once thought. The advent of exon and tiling microarrays means that researchers now have the capacity to experimentally measure alternative splicing on a genome wide level. New methods are needed to analyze the data from these arrays.Results: We present a method, finding isoforms using robust multichip analysis (FIRMA), for detecting differential alternative splicing in exon array data. FIRMA has been developed for Affymetrix exon arrays, but could in principle be extended to other exon arrays, tiling arrays or splice junction arrays. We have evaluated the method using simulated data, and have also applied it to two datasets: a panel of 11 human tissues and a set of 10 pairs of matched normal and tumor colon tissue. FIRMA is able to detect exons in several genes confirmed by reverse transcriptase PCR.Availability: R code implementing our methods is contributed to the package aroma.affymetrix.Contact: epurdom@stat.berkeley.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Detecting differential usage of exons from RNA-seq data

“…Robinson et al (2010a) extended edgeR with generalized linear models (GLMs) and the Cox-Reid dispersion estimator, discussed below. The basic approach of using exoncondition interactions in linear or generalized linear models to detect differential exon usage has been explored before by Cline et al (2005) and Purdom et al (2008) for exon microarrays and by Blekhman et al (2010) for RNA-seq data. Our method can be seen as a further development of these approaches that also incorporated ideas from DESeq (Anders and Huber 2010).…”

Detecting differential usage of exons from RNA-Seq data

“…Robinson et al (2010a) extended edgeR with generalized linear models (GLMs) and the Cox-Reid dispersion estimator, discussed later. The basic approach of using exon-condition interactions in linear or generalized linear models to detect differential exon usage has been explored before by Cline et al (2005) and Purdom et al (2008) for exon microarrays and by Blekhman et al (2010) for RNA-Seq data. Our approach can be seen as a further development of these approaches that also incorporated ideas from DESeq (Anders and Huber, 2010).…”

Gene expression changes in normal haematopoietic cells

“…82 Capitalizing on these data, more sophisticated microarrays are being developed that will allow researchers to discriminate between isoforms and quantify alternative splicing. 97,98 At the level of the proteome, the most basic question is whether or not a protein is present within a cell or in a comparison of cell lysates. Two-dimensional protein electrophoresis (2DPE), based on separation of proteins first by isoelectic point and then by denaturation electrophoresis, provided the first insight into differential protein expression in a holistic fashion.…”