Dataset Information

RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays.

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.

SUBMITTER: Seok J

PROVIDER: S-EPMC4491729 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Publications

RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays.

Seok Junhee J Xu Weihong W Davis Ronald W RW Xiao Wenzhong W

Scientific reports 20150706

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 th ...[more]

PMID: 26145443

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Project description:BACKGROUND: Commercially available microarrays have been used in many settings to generate expression profiles for a variety of applications, including target selection for disease detection, classification, profiling for pharmacogenomic response to therapeutics, and potential disease staging. However, many commercially available microarray platforms fail to capture transcript diversity produced by alternative splicing, a major mechanism for driving proteomic diversity through transcript heterogeneity. RESULTS: The human Genome-Wide SpliceArray(TM) (GWSA), a novel microarray platform, utilizes an existing probe design concept to monitor such transcript diversity on a genome scale. The human GWSA allows the detection of alternatively spliced events within the human genome through the use of exon body and exon junction probes to provide a direct measure of each transcript, through simple calculations derived from expression data. This report focuses on the performance and validation of the array when measured against standards recently published by the Microarray Quality Control (MAQC) Project. The array was shown to be highly quantitative, and displayed greater than 85% correlation with the HG-U133 Plus 2.0 array at the gene level while providing more extensive coverage of each gene. Almost 60% of splice events among genes demonstrating differential expression of greater than 3 fold also contained extensive splicing alterations. Importantly, almost 10% of splice events within the gene set displaying constant overall expression values had evidence of transcript diversity. Two examples illustrate the types of events identified: LIM domain 7 showed no differential expression at the gene level, but demonstrated deregulation of an exon skip event, while erythrocyte membrane protein band 4.1 -like 3 was differentially expressed and also displayed deregulation of a skipped exon isoform. CONCLUSION: Significant changes were detected independent of transcriptional activity, indicating that the controls for transcript generation and transcription are distinct, and require novel tools in order to detect changes in specific transcript quantity. Our results demonstrate that the SpliceArray(TM) design will provide researchers with a robust platform to detect and quantify specific changes not only in overall gene expression, but also at the individual transcript level.

Dataset Information

RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays.

Publications

RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays.

Similar Datasets

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