Abstract
Human transcriptome arrays (HTA) have recently been developed for high-throughput alternative splicing analysis by measuring signals not only from exons but also from exon-exon junctions. Effective use of these rich signals requires the development of computational methods for better gene and alternative splicing analyses. In this work, we introduce a computational method, Robust Alternative Splicing Analysis (RASA), for the analysis of the new transcriptome arrays by effective integration of the exon and junction signals. To increase robustness, RASA calculates the expression of each gene by selecting exons classified as not alternatively spliced. It then identifies alternatively spliced exons that are supported by both exon and junction signals to reduce the false positives. Finally, it detects additional alternative splicing candidates that are supported by only exon signals because the signals from the corresponding junctions are not well detected. RASA was demonstrated with Affymetrix HTAs and its performance was evaluated with mRNA-Seq and RT-PCR. The validation rate is 52.4%, which is a 60% increase when compared with previous methods that do not use selected exons for gene expression calculation and junction signals for splicing detection. These results suggest that RASA significantly improves alternative splicing analyses on HTA platforms.
Highlights
Constitutive exons of a gene are defined as exons that are not alternatively spliced across conditions, and the remaining exons of the gene are putatively alternative
Following standard protocols suggested by the manufacturer, three replicates of human liver and muscle tissue samples were hybridized on Affymetrix HTA 1.0, previously high-density human exon junction array, HJAY24
In the analysis of microarray data, accurately calculating gene expression indices is essential because an alternative splicing event between two groups of samples in a study is detected by comparing the changes in expression indices of an exon or a junction relative to the changes in the expression of the corresponding gene[16,18,19]
Summary
Constitutive exons of a gene are defined as exons that are not alternatively spliced across conditions, and the remaining exons of the gene are putatively alternative. For a simple comparison of two conditions, first, exons absent in any condition are marked as putatively alternative (group DABG p-value > 0.01 in this work). One is marked as an outlier if its expression fold change falls outside of [m − ds, m + ds], where m and s are the mean and standard deviation of exon expression fold changes respectively, and d is a pre-defined sensitivity parameter. M and s are calculated again with non-outlier exons and outliers are updated. This process is repeated until outliers converge into a fixed set, which becomes to be additional putatively alternative exons. The gene expression is calculated from probes of the remaining putatively constitutive exons
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