Literature DB >> 22589127

Detection and quantification of alternative splicing variants using RNA-seq.

Douglas W Bryant1, Henry D Priest, Todd C Mockler.   

Abstract

Next-generation sequencing has enabled genome-wide studies of alternative pre-mRNA splicing, allowing for empirical determination, characterization, and quantification of the expressed RNAs in a sample in toto. As a result, RNA sequencing (RNA-seq) has shown tremendous power to drive biological discoveries. At the same time, RNA-seq has created novel challenges that necessitate the development of increasingly sophisticated computational approaches and bioinformatic tools. In addition to the analysis of massive datasets, these tools also need to facilitate questions and analytical approaches driven by such rich data. HTS and RNA-seq are still in a stage of very rapid evolution and are, therefore, only introduced in general terms. This chapter mainly focuses on the methods for discovery, detection, and quantification of alternatively spliced transcript variants.

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Year:  2012        PMID: 22589127     DOI: 10.1007/978-1-61779-839-9_7

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


  8 in total

1.  Alternative Splicing Detection Tool-a novel PERL algorithm for sensitive detection of splicing events, based on next-generation sequencing data analysis.

Authors:  Panagiotis G Adamopoulos; Margarita C Theodoropoulou; Andreas Scorilas
Journal:  Ann Transl Med       Date:  2018-06

Review 2.  Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation.

Authors:  Yongsheng Li; Daniel J McGrail; Juan Xu; Gordon B Mills; Nidhi Sahni; Song Yi
Journal:  Trends Biochem Sci       Date:  2018-06-22       Impact factor: 13.807

3.  In silico prediction of splice-altering single nucleotide variants in the human genome.

Authors:  Xueqiu Jian; Eric Boerwinkle; Xiaoming Liu
Journal:  Nucleic Acids Res       Date:  2014-12-16       Impact factor: 16.971

4.  A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples.

Authors:  Sven Schuierer; Walter Carbone; Judith Knehr; Virginie Petitjean; Anita Fernandez; Marc Sultan; Guglielmo Roma
Journal:  BMC Genomics       Date:  2017-06-05       Impact factor: 3.969

5.  RNA-Seq Analysis of Differential Splice Junction Usage and Intron Retentions by DEXSeq.

Authors:  Yafang Li; Xiayu Rao; William W Mattox; Christopher I Amos; Bin Liu
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

6.  TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.

Authors:  Neelima Chitturi; Govindkumar Balagannavar; Darshan S Chandrashekar; Sadashivam Abinaya; Vasan S Srini; Kshitish K Acharya
Journal:  BMC Genomics       Date:  2013-12-27       Impact factor: 3.969

7.  Improved definition of the mouse transcriptome via targeted RNA sequencing.

Authors:  Giovanni Bussotti; Tommaso Leonardi; Michael B Clark; Tim R Mercer; Joanna Crawford; Lorenzo Malquori; Cedric Notredame; Marcel E Dinger; John S Mattick; Anton J Enright
Journal:  Genome Res       Date:  2016-05       Impact factor: 9.043

8.  Automation of Spatial Transcriptomics library preparation to enable rapid and robust insights into spatial organization of tissues.

Authors:  Emelie Berglund; Sami Saarenpää; Anders Jemt; Joel Gruselius; Ludvig Larsson; Ludvig Bergenstråhle; Joakim Lundeberg; Stefania Giacomello
Journal:  BMC Genomics       Date:  2020-04-15       Impact factor: 3.969

  8 in total

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