School of Mathematics and Statistics, Shandong University (Weihai), Weihai 264209, China.
Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China.
Genome Res. 2020 Aug;30(8):1181-1190. doi: 10.1101/gr.257766.119. Epub 2020 Aug 17.
RNA-seq technology is widely used in various transcriptomic studies and provides great opportunities to reveal the complex structures of transcriptomes. To effectively analyze RNA-seq data, we introduce a novel transcriptome assembler, TransBorrow, which borrows the assemblies from different assemblers to search for reliable subsequences by building a colored graph from those borrowed assemblies. Then, by seeding reliable subsequences, a newly designed path extension strategy accurately searches for a transcript-representing path cover over each splicing graph. TransBorrow was tested on both simulated and real data sets and showed great superiority over all the compared leading assemblers.
RNA-seq 技术广泛应用于各种转录组学研究,为揭示转录组的复杂结构提供了极好的机会。为了有效地分析 RNA-seq 数据,我们引入了一种新的转录组组装工具 TransBorrow,它从不同的组装工具中借用组装结果,通过构建一个从这些借来的组装结果中构建的有色图来搜索可靠的子序列。然后,通过播种可靠的子序列,一个新设计的路径扩展策略可以在每个拼接图上准确地搜索代表转录本的路径覆盖。TransBorrow 在模拟和真实数据集上进行了测试,显示出比所有比较领先的组装工具都具有更大的优越性。