A survey of software for genome-wide discovery of differential splicing in RNA-Seq data.
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.
Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, 12801 17th Ave, rm 12103, MS 8108, PO Box 6511, Aurora, CO 80045, USA. joan.hooper@ucdenver.edu.
Joan E
JE
Hooper
D017398:Alternative Splicing / Q000235:genetics*; D001483:Base Sequence; D005091:Exons / Q000235:genetics; D005786:Gene Expression Regulation; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software
D012313:RNA