Chapter title |
RNA Modification Detection Using Nanopore Direct RNA Sequencing and nanoDoc2.
|
---|---|
Chapter number | 21 |
Book title |
Nanopore Sequencing
|
Published in |
Methods in molecular biology, January 2023
|
DOI | 10.1007/978-1-0716-2996-3_21 |
Pubmed ID | |
Book ISBNs |
978-1-07-162995-6, 978-1-07-162996-3
|
Authors |
Ueda, Hiroki, Dasgupta, Bhaskar, Yu, Bo-Yi, Yu, Bo-yi |
Abstract |
RNA modifications regulate multiple aspects of cellular function including RNA splicing, translation, export, decay, stability, and phase separation. One of the comprehensive ways to detect such modifications is by the recent advancement of direct RNA sequencing from Oxford Nanopore Technologies (ONT). However, this method obtains a large amount of data with high complexity in the form of raw current signal that poses a new informatics challenge to accurately detect those modifications. Here, we provide nanoDoc2, a software to detect multiple types of RNA modification from nanopore direct RNA sequencing data. The nanoDoc2 includes a novel signal segmentation algorithm based on the trace value-a base probability feature that is added by the Guppy basecalling program from ONT during processing of the raw signal. The core of nanoDoc2 includes a machine learning algorithm in which a 6-mer segmented raw current signal is analyzed by deep one-class classification using a WaveNet-based neural network. As an output, an RNA modification is detected by a statistical score in each candidate position. Herein, we describe the detailed instructions on how to use nanoDoc2 for signal segmentation, train/test the neural network, and finally predict RNA modifications present in nanopore direct RNA sequencing data. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 7 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 29% |
Unspecified | 1 | 14% |
Student > Bachelor | 1 | 14% |
Student > Doctoral Student | 1 | 14% |
Unknown | 2 | 29% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 2 | 29% |
Biochemistry, Genetics and Molecular Biology | 1 | 14% |
Unspecified | 1 | 14% |
Unknown | 3 | 43% |