| Chapter title |
Comparison of Gene Expression Profiles in Nonmodel Eukaryotic Organisms with RNA-Seq
|
|---|---|
| Chapter number | 1 |
| Book title |
Transcriptome Data Analysis
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7710-9_1 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7709-3, 978-1-4939-7710-9
|
| Authors |
Han Cheng, Yejun Wang, Ming-an Sun |
| Abstract |
With recent advances of next-generation sequencing technology, RNA-Sequencing (RNA-Seq) has emerged as a powerful approach for the transcriptomic profiling. RNA-Seq has been used in almost every field of biological studies, and has greatly extended our view of transcriptomic complexity in different species. In particular, for nonmodel organisms which are usually without high-quality reference genomes, the de novo transcriptome assembly from RNA-Seq data provides a solution for their comparative transcriptomic study. In this chapter, we focus on the comparative transcriptomic analysis of nonmodel organisms. Two analysis strategies (without or with reference genome) are described step-by-step, with the differentially expressed genes explored. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 19% |
| Student > Ph. D. Student | 2 | 13% |
| Student > Doctoral Student | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Unspecified | 1 | 6% |
| Other | 3 | 19% |
| Unknown | 5 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 38% |
| Biochemistry, Genetics and Molecular Biology | 2 | 13% |
| Unspecified | 1 | 6% |
| Environmental Science | 1 | 6% |
| Immunology and Microbiology | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 4 | 25% |