Projects per year
Abstract
Transcription of eukaryotic genomes involves complex alternative processing of RNAs. Sequencing of full-length RNAs using long reads reveals the true complexity of processing. However, the relatively high error rates of long-read sequencing technologies can reduce the accuracy of intron identification. Here we apply alignment metrics and machine-learning-derived sequence information to filter spurious splice junctions from long read alignments and use the remaining junctions to guide realignment in a two-pass approach. This method, available in the software package 2passtools (https://github.com/bartongroup/2passtools), improves the accuracy of spliced alignment and transcriptome assembly for species both with and without existing high-quality annotations.
Original language | English |
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Article number | 72 |
Number of pages | 24 |
Journal | Genome Biology |
Volume | 22 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Mar 2021 |
Keywords
- splicing
- long read sequencing
- spliced alignment
- RNA-seq
- gene expression
- transcriptome assembly
- machine learning
- nanopore
- Splicing
- Long-read sequencing
- Gene expression
- Transcriptome assembly
- Nanopore sequencing
- Machine learning
- Spliced alignment
ASJC Scopus subject areas
- Genetics
- Ecology, Evolution, Behavior and Systematics
- Cell Biology
Fingerprint
Dive into the research topics of '2passtools: two-pass alignment using machine-learning-filtered splice junctions increases the accuracy of intron detection in long-read RNA sequencing'. Together they form a unique fingerprint.Projects
- 5 Finished
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Diversifying Transcription Termination Function
Biotechnology and Biological Sciences Research Council
1/06/15 → 31/05/19
Project: Research
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The Arabidopsis Epitranscriptome (Joint with University of Nottingham)
Biotechnology and Biological Sciences Research Council
1/04/15 → 31/03/19
Project: Research
Research output
- 9 Citations
- 1 Preprint
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Two-pass alignment using machine-learning-filtered splice junctions increases the accuracy of intron detection in long-read RNA sequencing
Parker, M. T., Barton, G. J. & Simpson, G. G., 30 May 2020, Cold Spring Harbor Laboratory: BioRxiv, 36 p.Research output: Working paper/Preprint › Preprint
Datasets
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Nanopore direct RNA sequencing of the Arabidopsis RNA exosome mutant hen2-2
Parker, M. (Creator), Knop, K. (Creator), Barton, G. (Creator) & Simpson, G. (Creator), European Nucleotide Archive, 16 Dec 2020
https://www.ebi.ac.uk/ena/browser/view/PRJEB41381
Dataset