| Chapter title |
Next-generation whole genome sequencing of dengue virus.
|
|---|---|
| Chapter number | 12 |
| Book title |
Dengue
|
| Published in |
Methods in molecular biology, January 2014
|
| DOI | 10.1007/978-1-4939-0348-1_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-0347-4, 978-1-4939-0348-1
|
| Authors |
Pauline Poh Kim Aw, Paola Florez de Sessions, Andreas Wilm, Long Truong Hoang, Niranjan Nagarajan, October M Sessions, Martin Lloyd Hibberd, October M. Sessions, Aw, Pauline Poh Kim, Sessions, Paola Florez, Wilm, Andreas, Hoang, Long Truong, Nagarajan, Niranjan, Sessions, October M., Hibberd, Martin Lloyd, Sessions, Paola Florez de |
| Abstract |
RNA viruses are notorious for their ability to quickly adapt to selective pressure from the host immune system and/or antivirals. This adaptability is likely due to the error-prone characteristics of their RNA-dependent, RNA polymerase [1, 2]. Dengue virus, a member of the Flaviviridae family of positive-strand RNA viruses, is also known to share these error-prone characteristics [3]. Utilizing high-throughput, massively parallel sequencing methodologies, or next-generation sequencing (NGS), we can now accurately quantify these populations of viruses and track the changes to these populations over the course of a single infection. The aim of this chapter is twofold: to describe the methodologies required for sample preparation prior to sequencing and to describe the bioinformatics analyses required for the resulting data. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 54 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 21% |
| Researcher | 10 | 18% |
| Student > Bachelor | 7 | 13% |
| Student > Master | 7 | 13% |
| Student > Doctoral Student | 4 | 7% |
| Other | 7 | 13% |
| Unknown | 9 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 21% |
| Immunology and Microbiology | 10 | 18% |
| Biochemistry, Genetics and Molecular Biology | 7 | 13% |
| Medicine and Dentistry | 7 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Other | 6 | 11% |
| Unknown | 12 | 21% |