Literature DB >> 24549677

Methods to study splicing from high-throughput RNA sequencing data.

Gael P Alamancos1, Eneritz Agirre, Eduardo Eyras.   

Abstract

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data, which could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.

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Year:  2014        PMID: 24549677     DOI: 10.1007/978-1-62703-980-2_26

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  35 in total

Review 1.  RNA-Seq technology and its application in fish transcriptomics.

Authors:  Xi Qian; Yi Ba; Qianfeng Zhuang; Guofang Zhong
Journal:  OMICS       Date:  2013-12-31

2.  rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

Authors:  Shihao Shen; Juw Won Park; Zhi-xiang Lu; Lan Lin; Michael D Henry; Ying Nian Wu; Qing Zhou; Yi Xing
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-05       Impact factor: 11.205

3.  Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data.

Authors:  Alexander Kanitz; Foivos Gypas; Andreas J Gruber; Andreas R Gruber; Georges Martin; Mihaela Zavolan
Journal:  Genome Biol       Date:  2015-07-23       Impact factor: 13.583

4.  IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity.

Authors:  Wei Sun; Yufeng Liu; James J Crowley; Ting-Hued Chen; Hua Zhou; Haitao Chu; Shunping Huang; Pei-Fen Kuan; Yuan Li; Darla R Miller; Ginger D Shaw; Yichao Wu; Vasyl Zhabotynsky; Leonard McMillan; Fei Zou; Patrick F Sullivan; Fernando Pardo-Manuel de Villena
Journal:  J Am Stat Assoc       Date:  2015-11-07       Impact factor: 5.033

5.  Increased Alternative Splicing as a Host Response to Edwardsiella ictaluri Infection in Catfish.

Authors:  Suxu Tan; Wenwen Wang; Xiaoxiao Zhong; Changxu Tian; Donghong Niu; Lisui Bao; Tao Zhou; Yulin Jin; Yujia Yang; Zihao Yuan; Dongya Gao; Rex Dunham; Zhanjiang Liu
Journal:  Mar Biotechnol (NY)       Date:  2018-07-16       Impact factor: 3.619

6.  SUVA: splicing site usage variation analysis from RNA-seq data reveals highly conserved complex splicing biomarkers in liver cancer.

Authors:  Chao Cheng; Lei Liu; Yongli Bao; Jingwen Yi; Weili Quan; Yaqiang Xue; Luguo Sun; Yi Zhang
Journal:  RNA Biol       Date:  2021-06-21       Impact factor: 4.766

7.  Transcriptome changes in rice (Oryza sativa L.) in response to high night temperature stress at the early milky stage.

Authors:  Jiang-Lin Liao; Hui-Wen Zhou; Qi Peng; Ping-An Zhong; Hong-Yu Zhang; Chao He; Ying-Jin Huang
Journal:  BMC Genomics       Date:  2015-01-23       Impact factor: 3.969

8.  Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium.

Authors:  Nancy Yiu-Lin Yu; Björn M Hallström; Linn Fagerberg; Fredrik Ponten; Hideya Kawaji; Piero Carninci; Alistair R R Forrest; Yoshihide Hayashizaki; Mathias Uhlén; Carsten O Daub
Journal:  Nucleic Acids Res       Date:  2015-06-27       Impact factor: 16.971

Review 9.  RNA splicing factors as oncoproteins and tumour suppressors.

Authors:  Heidi Dvinge; Eunhee Kim; Omar Abdel-Wahab; Robert K Bradley
Journal:  Nat Rev Cancer       Date:  2016-06-10       Impact factor: 60.716

10.  Computational comparison of common event-based differential splicing tools: practical considerations for laboratory researchers.

Authors:  Ittai B Muller; Stijn Meijers; Peter Kampstra; Steven van Dijk; Michel van Elswijk; Marry Lin; Anna M Wojtuszkiewicz; Gerrit Jansen; Robert de Jonge; Jacqueline Cloos
Journal:  BMC Bioinformatics       Date:  2021-06-26       Impact factor: 3.169

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