title: SplicingTypesAnno: annotating and quantifying alternative splicing events for RNA-Seq data.
abstract: Alternative splicing plays a key role in the regulation of the central dogma. Four major types of alternative splicing have been classified as intron retention, exon skipping, alternative 5 splice sites or alternative donor sites, and alternative 3 splice sites or alternative acceptor sites. A few algorithms have been developed to detect splice junctions from RNA-Seq reads. However, there are few tools targeting at the major alternative splicing types at the exon/intron level. This type of analysis may reveal subtle, yet important events of alternative splicing, and thus help gain deeper understanding of the mechanism of alternative splicing. This paper describes a user-friendly R package, extracting, annotating and analyzing alternative splicing types for sequence alignment files from RNA-Seq. SplicingTypesAnno can: (1) provide annotation for major alternative splicing at exon/intron level. By comparing the annotation from GTF/GFF file, it identifies the novel alternative splicing sites; (2) offer a convenient two-level analysis: genome-scale annotation for users with high performance computing environment, and gene-scale annotation for users with personal computers; (3) generate a user-friendly web report and additional BED files for IGV visualization. SplicingTypesAnno is a user-friendly R package for extracting, annotating and analyzing alternative splicing types at exon/intron level for sequence alignment files from RNA-Seq. It is publically available at https://sourceforge.net/projects/splicingtypes/files/ or http://genome.sdau.edu.cn/research/software/SplicingTypesAnno.html.
authors.affiliation: Agricultural Big-Data Research Center, College of Information Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China. Electronic address: johnsunx1@gmail.com.
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Sun
authors.affiliation: College of Information Engineering, Taishan Medical University, Taian, Shandong 271000, China.
authors.forename: Fenghua
authors.initials: F
authors.lastname: Zuo
authors.affiliation: Department of Biomedical Informatics, Windber Research Institute, Windber, PA 15963, USA.
authors.forename: Yuanbin
authors.initials: Y
authors.lastname: Ru
authors.affiliation: Applied Statistics Center, Columbia University, New York, NY 10027, USA.
authors.forename: Jiqiang
authors.initials: J
authors.lastname: Guo
authors.affiliation: Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No. 42 Wenhua West Road, Jinan, Shandong 250011, China.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Yan
authors.affiliation: Plant Functional Biology and Climate Change Cluster (C3), University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia.
authors.forename: Gaurav
authors.initials: G
authors.lastname: Sablok
mesh_terms: D017398:Alternative Splicing; D000818:Animals; D019295:Computational Biology; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D058977:Molecular Sequence Annotation / Q000706:statistics & numerical data; D017423:Sequence Analysis, RNA / Q000706:statistics & numerical data*; D012984:Software
keywords: Gene-scale annotation; Genome-scale annotation; R package; Splicing junction