TransRef enables accurate transcriptome assembly by redefining accurate neo-splicing graphs. Issue 6 (13th July 2021)

• Record Type: Journal Article
• Authors: Yu, Ting; Han, Renmin; Fang, Zhaoyuan; Mu, Zengchao; Zheng, Hongyu; Liu, Juntao
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 6(2021)
• Publication Date: 2021-07-13
• Subjects: transcriptome assembly -- RNA-seq reads -- neo-splicing graphs -- genome-guided assembly -- reference annotations; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbab261
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: RNA-seq technology is widely employed in various research areas related to transcriptome analyses, and the identification of all the expressed transcripts from short sequencing reads presents a considerable computational challenge. In this study, we introduce TransRef, a new computational algorithm for accurate transcriptome assembly by redefining a novel graph model, the neo-splicing graph, and then iteratively applying a constrained dynamic programming to reconstruct all the expressed transcripts for each graph. When TransRef is utilized to analyze both real and simulated datasets, its performance is notably better than those of several state-of-the-art assemblers, including StringTie2, Cufflinks and Scallop. In particular, the performance of TransRef is notably strong in identifying novel transcripts and transcripts with low-expression levels, while the other assemblers are less effective.