| Chapter title |
Oogenesis
|
|---|---|
| Chapter number | 10 |
| Book title |
Oogenesis
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3795-0_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3793-6, 978-1-4939-3795-0
|
| Authors |
Carter, Jean-Michel, Gibbs, Melanie, Breuker, Casper J, Jean-Michel Carter, Melanie Gibbs, Casper J. Breuker |
| Editors |
Ioannis P. Nezis |
| Abstract |
This chapter provides a guide to processing and analyzing RNA-Seq data in a non-model organism. This approach was implemented for studying oogenesis in the Speckled Wood Butterfly Pararge aegeria. We focus in particular on how to perform a more informative primary annotation of your non-model organism by implementing our multi-BLAST annotation strategy. We also provide a general guide to other essential steps in the next-generation sequencing analysis workflow. Before undertaking these methods, we recommend you familiarize yourself with command line usage and fundamental concepts of database handling. Most of the operations in the primary annotation pipeline can be performed in Galaxy (or equivalent standalone versions of the tools) and through the use of common database operations (e.g. to remove duplicates) but other equivalent programs and/or custom scripts can be implemented for further automation. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 40% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 33% |
| Professor > Associate Professor | 1 | 17% |
| Student > Bachelor | 1 | 17% |
| Lecturer > Senior Lecturer | 1 | 17% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 33% |
| Agricultural and Biological Sciences | 2 | 33% |
| Computer Science | 1 | 17% |
| Unknown | 1 | 17% |