Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis

By J. Weirather, M. de Cesare, Yunhao Wang, P. Piazza, V. Sebastiano, Xiu-Jie Wang, D. Buck, Kin Fai Au. F1000Research, 2017

452 citations recorded by the source corpus.

Background: Given the demonstrated utility of Third Generation Sequencing [Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT)] long reads in many studies, a comprehensive analysis and comparison of their data quality and applications is in high demand. Methods: Based on the transcriptome sequencing data from human embryonic stem cells, we analyzed multiple data features of PacBio and ONT, including error pattern, length, mappability and technical improvements over previous platforms. We also evaluated their application to transcriptome analyses, such as isoform identification and quantification and characterization of transcriptome complexity, by comparing the performance of size-selected PacBio, non-size-selected ONT and their corresponding Hybrid-Seq strategies (PacBio+Illumina and ONT+Illumina). Results: PacBio shows overall better data quality, while ONT provides a higher yield. As with data quality, PacBio performs marginally better than ONT in most aspects for both long reads only and Hybrid-Seq strategies in transcriptome analysis. In addition, Hybrid-Seq shows superior performance over long reads only in most transcriptome analyses. Conclusions: Both PacBio and ONT sequencing are suitable for full-length single-molecule transcriptome analysis. As this first use of ONT reads in a Hybrid-Seq analysis has shown, both PacBio and ONT can benefit from a combined Illumina strategy. The tools and analytical methods developed here provide a resource for future applications and evaluations of these rapidly-changing technologies.

View Paper: https://www.semanticscholar.org/paper/4dd259f1135e539c4684e0cf1b25a8445c9a82b3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Long-read human genome sequencing and its applications (2020, unknown): “1; Supplementary Note), which is consistent with data reported elsewhere 31,41 44 .”
Improved transcriptome assembly using a hybrid of long and short reads with StringTie (2021, background): “Additionally, long reads have a high error rate relative to Illumina short reads [4], and the throughput of long-read RNA-seq is much lower than that of short-read RNA-seq.”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, background): “Encouragingly, a recent study showed that by combining LRTS and Illumina data, more accurate quantifications for the artificial SIRV transcripts could be achieved [203].”
Nanopore sequencing technology, bioinformatics and applications (2021, methodology): “A comprehensive examination of the feasibility of ONT cDNA sequencing (with R7 and R9 nanopores) in transcriptome analyses demonstrated its similar performance in gene isoform identification to PacBio long reads, both of which are superior to Illumina short reads 42 .”
TGS-GapCloser: A fast and accurate gap closer for large genomes with low coverage of error-prone long reads (2020, unknown): “Although the cost has been decreasing [32], the gap-closing efficiency is still the first priority, particularly for small laboratories or small projects.”