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Computational methods for RNA modification detection from nanopore direct RNA sequencing data

Authors :
Furlan, M
Delgado-Tejedor, A
Mulroney, L
Pelizzola, M
Novoa, E
Leonardi, T
Furlan M
Delgado-Tejedor A
Mulroney L
Pelizzola M
Novoa EM
Leonardi T
Furlan, M
Delgado-Tejedor, A
Mulroney, L
Pelizzola, M
Novoa, E
Leonardi, T
Furlan M
Delgado-Tejedor A
Mulroney L
Pelizzola M
Novoa EM
Leonardi T
Publication Year :
2021

Abstract

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms.

Details

Database :
OAIster
Notes :
STAMPA, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1415731080
Document Type :
Electronic Resource