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    ABSTRACT: The vast majority of multi-exon genes in higher eukaryotes are alternatively spliced and changes in alternative splicing (AS) can impact gene function or cause disease. High-throughput RNA sequencing (RNA-seq) has become a powerful technology for transcriptome-wide analysis of AS, but RT-PCR still remains the gold-standard approach for quantifying and validating exon splicing levels. We have developed PrimerSeq, a user-friendly software for systematic design and visualization of RT-PCR primers using RNA-seq data. PrimerSeq incorporates user-provided transcriptome profiles (i.e., RNA-seq data) in the design process, and is particularly useful for large-scale quantitative analysis of AS events discovered from RNA-seq experiments. PrimerSeq features a graphical user interface (GUI) that displays the RNA-seq data juxtaposed with the expected RT-PCR results. To enable primer design and visualization on user-provided RNA-seq data and transcript annotations, we have developed PrimerSeq as a stand-alone software that runs on local computers. PrimerSeq is freely available for Windows and Mac OS X along with source code at http://primerseq.sourceforge.net/. With the growing popularity of RNA-seq for transcriptome studies, we expect PrimerSeq to help bridge the gap between high-throughput RNA-seq discovery of AS events and molecular analysis of candidate events by RT-PCR.
    Genomics Proteomics & Bioinformatics 01/2014;
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    ABSTRACT: Alternative splicing is a major contributor to cellular diversity. Therefore the identification and quantification of differentially spliced transcripts in genome-wide transcript analysis is an important consideration. Here, I review the software available for analysis of RNA-Seq data for differential splicing and discuss intrinsic challenges for differential splicing analyses. Three approaches to differential splicing analysis are described, along with their associated software implementations, their strengths, limitations, and caveats. Suggestions for future work include more extensive experimental validation to assess accuracy of the software predictions and consensus formats for outputs that would facilitate visualizations, data exchange, and downstream analyses.
    Human genomics 01/2014; 8(1):3.
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    ABSTRACT: RNA-seq data is currently underutilized, in part because it is difficult to predict the functional impact of alternate transcription events. Recent software improvements in full-length transcript deconvolution prompted us to develop spliceR, an R package for classification of alternative splicing and prediction of coding potential. spliceR uses the full-length transcript output from RNA-seq assemblers to detect single or multiple exon skipping, alternative donor and acceptor sites, intron retention, alternative first or last exon usage, and mutually exclusive exon events. For each of these events spliceR also annotates the genomic coordinates of the differentially spliced elements, facilitating downstream sequence analysis. For each transcript isoform fraction values are calculated to identify transcript switching between conditions. Lastly, spliceR predicts the coding potential, as well as the potential nonsense mediated decay (NMD) sensitivity of each transcript. spliceR is an easy-to-use tool that extends the usability of RNA-seq and assembly technologies by allowing greater depth of annotation of RNA-seq data. spliceR is implemented as an R package and is freely available from the Bioconductor repository (http://www.bioconductor.org/packages/2.13/bioc/html/spliceR.html).
    BMC Bioinformatics 03/2014; 15(1):81. · 3.02 Impact Factor

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