ArticleMethods in molecular biology (Clifton, N.J.)2023
Nanopore Direct RNA Sequencing Data Processing and Analysis Using MasterOfPores.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Systematic benchmarking of dorado basecalling models for RNA modification detection with highly multiplexed nanopore sequencing.Nucleic acids research · 2026Article
- Transcriptomics in the era of long-read sequencing.Nature reviews. Genetics · 2025Review
- Rapid and accurate demultiplexing of direct RNA nanopore sequencing data with SeqTagger.Genome research · 2025Article
- De novo basecalling of RNA modifications at single molecule and nucleotide resolution.Genome biology · 2025Article
- Native RNA nanopore sequencing reveals antibiotic-induced loss of rRNA modifications in the A- and P-sites.Nature communications · 2024Article
- Enhanced detection of RNA modifications and read mapping with high-accuracy nanopore RNA basecalling models.Genome research · 2024Article
- Nuclear localization of MTHFD2 is required for correct mitosis progression.Nature communications · 2024Article
- NNature communications · 2024Article
- Oxford Nanopore Technology and its Application in Liquid Biopsies.Current genomics · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
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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/MOP2 and is distributed under the MIT license.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.