Computational Approaches for Studying Alternative Splicing in Nonmodel Organisms from RNA‐SEQ Data
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© 2016 by John Wiley & Sons, Inc. All rights reserved. As the amount of data on RNA splicing increases rapidly due to advance in high-throughput sequencing, alternative splicing has become one of the most important mechanisms to study in nonmodel organisms. It is crucial to a variety of biological functions, including sex determination, immunity, chromatin remodeling, growth and development, tissue assembly, and tissue organization. The advance in high-throughput sequencing allows the creation of RNA-Seq libraries that contain a large number of reads from all expressed mRNAs. In high-throughput sequencing, a popular strategy of transcriptome assembly in nonmodel organisms is to first construct a de Bruijn graph that contains all branching possibilities from the reads. One possible strategy to study differences in alternative splicing and to obtain possible function of predicted transcripts in nonmodel organisms is to compare to the closest model organism by performing translated BLAST search. To further improve performance, new techniques have to be developed to address complications regarding repeats and gene families.
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Computational Methods for Next Generation Sequencing Data Analysis