Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data. Issue 6 (10th June 2020)

• Record Type: Journal Article
• Authors: Hafezqorani, Saber; Yang, Chen; Lo, Theodora; Nip, Ka Ming; Warren, René L; Birol, Inanc
• Is Part Of: GigaScience. Volume 9:Issue 6(2020)
• Publication Date: 2020-06-10
• Subjects: nanopore sequencing -- sequence simulation -- transcriptome -- RNA-seq; Information storage and retrieval systems -- Research -- Periodicals; Biology -- Research -- Periodicals; Medical sciences -- Research -- Periodicals; Database management -- Periodicals; 570.285
• DOI: 10.1093/gigascience/giaa061
• Languages: English
• ISSNs: 2047-217X

Abstract

Abstract: Background: Compared with second-generation sequencing technologies, third-generation single-molecule RNA sequencing has unprecedented advantages; the long reads it generates facilitate isoform-level transcript characterization. In particular, the Oxford Nanopore Technology sequencing platforms have become more popular in recent years owing to their relatively high affordability and portability compared with other third-generation sequencing technologies. To aid the development of analytical tools that leverage the power of this technology, simulated data provide a cost-effective solution with ground truth. However, a nanopore sequence simulator targeting transcriptomic data is not available yet. Findings: We introduce Trans-NanoSim, a tool that simulates reads with technical and transcriptome-specific features learnt from nanopore RNA-sequncing data. We comprehensively benchmarked Trans-NanoSim on direct RNA and complementary DNA datasets describing human and mouse transcriptomes. Through comparison against other nanopore read simulators, we show the unique advantage and robustness of Trans-NanoSim in capturing the characteristics of nanopore complementary DNA and direct RNA reads. Conclusions: As a cost-effective alternative to sequencing real transcriptomes, Trans-NanoSim will facilitate the rapid development of analytical tools for nanopore RNA-sequencing data. Trans-NanoSim and its pre-trained models are freely accessible at https://github.com/bcgsc/NanoSim .