Publication:20230203121556
From Bioinformatics Core Wiki
| Publication | |
|---|---|
| URL | https://link.springer.com/protocol/10.1007/978-1-0716-2962-8_13 |
| Title | Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores |
| Book Title | Computational Epigenomics and Epitranscriptomics |
| Authors | Luca Cozzuto, Anna Delgado-Tejedor, Toni Hermoso Pulido, Eva Maria Novoa, Julia Ponomarenko |
| Date | 2023 |
| Publisher | Springer US
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| DOI | 10.1007/978-1-0716-2962-8_13
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Abstract:
This chapter describes MasterOfPores v.2 (MoP2), an open-source suite of pipelines for processing and analyzing direct RNA Oxford Nanopore sequencing data. The MoP2 relies on the Nextflow DSL2 framework and Linux containers, thus enabling reproducible data analysis in transcriptomic and epitranscriptomic studies. We introduce the key concepts of MoP2 and provide a step-by-step fully reproducible and complete example of how to use the workflow for the analysis of S. cerevisiae total RNA samples sequenced using MinION flowcells. The workflow starts with the pre-processing of raw FAST5 files, which includes basecalling, read quality control, demultiplexing, filtering, mapping, estimation of per-gene/transcript abundances, and transcriptome assembly, with support of the GPU computing for the basecalling and read demultiplexing steps. The secondary analyses of the workflow focus on the estimation of RNA poly(A) tail lengths and the identification of RNA modifications. The MoP2 code is available at https://github.com/biocorecrg/MOP2and is distributed under the MIT license.
This chapter describes MasterOfPores v.2 (MoP2), an open-source suite of pipelines for processing and analyzing direct RNA Oxford Nanopore sequencing data. The MoP2 relies on the Nextflow DSL2 framework and Linux containers, thus enabling reproducible data analysis in transcriptomic and epitranscriptomic studies. We introduce the key concepts of MoP2 and provide a step-by-step fully reproducible and complete example of how to use the workflow for the analysis of S. cerevisiae total RNA samples sequenced using MinION flowcells. The workflow starts with the pre-processing of raw FAST5 files, which includes basecalling, read quality control, demultiplexing, filtering, mapping, estimation of per-gene/transcript abundances, and transcriptome assembly, with support of the GPU computing for the basecalling and read demultiplexing steps. The secondary analyses of the workflow focus on the estimation of RNA poly(A) tail lengths and the identification of RNA modifications. The MoP2 code is available at https://github.com/biocorecrg/MOP2and is distributed under the MIT license.
| Annotation | Development of MoP2 |
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