Chapter title |
Exploring the RNA Editing Potential of RNA-Seq Data by ExpEdit
|
---|---|
Chapter number | 20 |
Book title |
RNA Bioinformatics
|
Published in |
Methods in molecular biology, December 2014
|
DOI | 10.1007/978-1-4939-2291-8_20 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2290-1, 978-1-4939-2291-8
|
Authors |
Mattia D'Antonio, Ernesto Picardi, Tiziana Castrignanò, Anna Maria D'Erchia, Graziano Pesole, Mattia D’Antonio, Anna Maria D’Erchia |
Editors |
Ernesto Picardi |
Abstract |
Revealing the impact of A-to-I RNA editing in RNA-Seq experiments is relevant in humans because RNA editing can influence gene expression. In addition, its deregulation has been linked to a variety of human diseases. Exploiting the RNA editing potential in complete RNA-Seq datasets, however, is a challenging task. Indeed, no dedicated software is available, and sometimes deep computational skills and appropriate hardware resources are required. To explore the impact of known RNA editing events in massive transcriptome sequencing experiments, we developed the ExpEdit web service application. In the present work, we provide an overview of ExpEdit as well as methodologies to investigate known RNA editing in human RNA-Seq datasets. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 17% |
Unknown | 5 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2 | 33% |
Professor | 1 | 17% |
Researcher | 1 | 17% |
Unknown | 2 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 1 | 17% |
Computer Science | 1 | 17% |
Agricultural and Biological Sciences | 1 | 17% |
Unknown | 3 | 50% |