Comparative analysis of de novo transcriptome assembly

作     者：CLARKE Kaitlin YANG Yi MARSH Ronald XIE LingLin ZHANG Ke K. 

作者机构：Bioinformatics CoreDepartment of PathologyUniversity of North Dakota Department of Computer ScienceUniversity of North Dakota Department of Biochemistry and Molecular BiologyUniversity of North Dakota 

出 版 物：《Science China(Life Sciences)》 (中国科学（生命科学英文版）)

年 卷 期：2013年第56卷第2期

页      面：156-162页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 071007[理学-遗传学] 

基　　金：supported by grants from the National Center for Research Resources (5P20RR016471-12) the National Institute of General Medical Sciences (8 P20 GM103442-12) from the National Institutes of Health the seed collaborative research grant from the Odegard School of Aerospace Sciences and the School of Medicine and Health Sciences at University of North Dakota 

主　　题：transcriptome assembly next-generation sequencing RNA-Seq De Bruijn graph overlap graph 

摘      要：The fast development of next-generation sequencing technology presents a major computational challenge for data processing and analysis.A fast algorithm,de Bruijn graph has been successfully used for genome DNA de novo assembly;nevertheless,its performance for transcriptome assembly is *** this study,we used both simulated and real RNA-Seq data,from either artificial RNA templates or human transcripts,to evaluate five de novo assemblers,ABySS,Mira,Trinity,Velvet and *** these assemblers,ABySS,Trinity,Velvet and Oases are all based on de Bruijn graph,and Mira uses an overlap graph *** numbers of RNA short reads were selected from the External RNA Control Consortium(ERCC) data and human chromosome 22.A number of statistics were then calculated for the resulting contigs from each *** experiment was repeated multiple times to obtain the mean statistics and standard error *** had relative good performance for both ERCC and human data,but it may not consistently generate full length *** was the fastest method but its assembly quality was *** gave a good rate for mapping its contigs onto human chromosome 22,but its computational speed is not *** results suggest that transcript assembly remains a challenge problem for bioinformatics ***,a novel assembler is in need for assembling transcriptome data generated by next generation sequencing technique.