Assessment of transcript reconstruction methods for RNA-seq

被引:9
|
作者
Steijger, Tamara [1 ]
Abril, Josep F. [2 ]
Engstrom, Par G. [1 ]
Kokocinski, Felix [3 ]
Hubbard, Tim J. [3 ]
Guigo, Roderic [4 ,5 ]
Harrow, Jennifer [3 ]
Bertone, Paul [1 ,6 ,7 ,8 ]
机构
[1] European Bioinformat Inst, European Mol Biol Lab, Cambridge, England
[2] Univ Barcelona, Fac Biol, Dept Genet, Barcelona, Spain
[3] Wellcome Trust Sanger Inst, Cambridge, England
[4] Ctr Genom Regulat, Barcelona, Spain
[5] Univ Pompeu Fabra, Barcelona, Spain
[6] European Mol Biol Lab, Genome Biol Unit, D-69012 Heidelberg, Germany
[7] European Mol Biol Lab, Dev Biol Unit, D-69012 Heidelberg, Germany
[8] Univ Cambridge, Wellcome Trust Med Res Council Cambridge Stem Cel, Cambridge, England
基金
英国惠康基金; 美国国家卫生研究院;
关键词
GENOME ANNOTATION; ISOFORM DISCOVERY; ACCURATE; QUANTIFICATION; GENERATION; ALIGNMENT;
D O I
10.1038/NMETH.2714
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression-level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations on transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.
引用
收藏
页码:1177 / +
页数:10
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