spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data

被引:76
|
作者
Vitting-Seerup, Kristoffer [1 ,2 ]
Porse, Bo Torben [2 ,3 ,4 ]
Sandelin, Albin [1 ,2 ]
Waage, Johannes [1 ,2 ,3 ,4 ]
机构
[1] Univ Copenhagen, Bioinformat Ctr, Dept Biol, DK-2200 Copenhagen, Denmark
[2] Univ Copenhagen, Biotech Res & Innovat Ctr, DK-2200 Copenhagen, Denmark
[3] Univ Copenhagen, Rigshosp, Fac Hlth Sci, Finsen Lab, DK-2200 Copenhagen, Denmark
[4] Univ Copenhagen, Fac Hlth Sci, Danish Stem Cell Ctr DanStem, DK-2200 Copenhagen, Denmark
来源
BMC BIOINFORMATICS | 2014年 / 15卷
关键词
spliceR; RNA-Seq; Alternative splicing; Nonsense mediated decay (NMD); Isoform switch; DIFFERENTIAL EXPRESSION; EVENTS; VISUALIZATION; BIOCONDUCTOR; TOOL;
D O I
10.1186/1471-2105-15-81
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: 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. Results: 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. Conclusions: 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).
引用
收藏
页数:7
相关论文
共 50 条
  • [21] GLiMMPS: robust statistical model for regulatory variation of alternative splicing using RNA-seq data
    Keyan Zhao
    Zhi-xiang Lu
    Juw Won Park
    Qing Zhou
    Yi Xing
    Genome Biology, 14
  • [22] GLiMMPS: robust statistical model for regulatory variation of alternative splicing using RNA-seq data
    Zhao, Keyan
    Lu, Zhi-xiang
    Park, Juw Won
    Zhou, Qing
    Xing, Yi
    GENOME BIOLOGY, 2013, 14 (07):
  • [23] ASGAL: aligning RNA-Seq data to a splicing graph to detect novel alternative splicing events
    Denti, Luca
    Rizzi, Raffaella
    Beretta, Stefano
    Della Vedova, Gianluca
    Previtali, Marco
    Bonizzoni, Paola
    BMC BIOINFORMATICS, 2018, 19
  • [24] ASNEO: identification of personalized alternative splicing based neoantigens with RNA-seq
    Zhang, Zhanbing
    Zhou, Chi
    Tang, Lihua
    Gong, Yukang
    Wei, Zhiting
    Zhang, Gongchen
    Wang, Feng
    Liu, Qi
    Yu, Jing
    AGING-US, 2020, 12 (14): : 14633 - 14648
  • [25] BingleSeq: a user-friendly R package for bulk and single-cell RNA-Seq data analysis
    Dimitrov, Daniel
    Gu, Quan
    PEERJ, 2020, 8
  • [26] SpliceJumper: a classification-based approach for calling splicing junctions from RNA-seq data
    Chong Chu
    Xin Li
    Yufeng Wu
    BMC Bioinformatics, 16
  • [27] ascend: R package for analysis of single-cell RNA-seq data
    Senabouth, Anne
    Lukowski, Samuel W.
    Hernandez, Jose Alquicira
    Andersen, Stacey B.
    Mei, Xin
    Nguyen, Quan H.
    Powell, Joseph E.
    GIGASCIENCE, 2019, 8 (08):
  • [28] Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package
    Tarazona, Sonia
    Furio-Tari, Pedro
    Turra, David
    Di Pietro, Antonio
    Jose Nueda, Maria
    Ferrer, Alberto
    Conesa, Ana
    NUCLEIC ACIDS RESEARCH, 2015, 43 (21)
  • [29] SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data
    Rogers, Mark F.
    Thomas, Julie
    Reddy, Anireddy S. N.
    Ben-Hur, Asa
    GENOME BIOLOGY, 2012, 13 (01):
  • [30] ToPASeq: an R package for topology-based pathway analysis of microarray and RNA-Seq data
    Ihnatova, Ivana
    Budinska, Eva
    BMC BIOINFORMATICS, 2015, 16