| Chapter title |
RNA-Seq as a Tool to Study the Tumor Microenvironment.
|
|---|---|
| Chapter number | 22 |
| Book title |
The Tumor Microenvironment
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3801-8_22 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3799-8, 978-1-4939-3801-8
|
| Authors |
Panichnantakul, Pudchalaluck, Bourgey, Mathieu, Montpetit, Alexandre, Bourque, Guillaume, Riazalhosseini, Yasser, Pudchalaluck Panichnantakul, Mathieu Bourgey, Alexandre Montpetit, Guillaume Bourque, Yasser Riazalhosseini |
| Editors |
Josie Ursini-Siegel, Nicole Beauchemin |
| Abstract |
The transcriptome is composed of different types of RNA molecules including mRNAs, tRNAs, rRNAs, and other noncoding RNAs that are found inside a cell at a given time. Analyzing transcriptome patterns can shed light on the functional state of the cell as well as on the dynamics of cellular behavior associated with genomic and environmental changes. Likewise, transcriptome analysis has been a major help in solving biological issues and understanding the molecular basis of many diseases including human cancers. Specifically, since targeted and whole genome sequencing studies are becoming more common in identifying the driving factors of cancer, a comprehensive and high-resolution analysis of the transcriptome, as provided by RNA-Sequencing (RNA-Seq), plays a key role in investigating the functional relevance of the identified genomic aberrations. Here, we describe experimental procedures of RNA-Seq and downstream data processing and analysis, with a focus on the identification of abnormally expressed transcripts and genes. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 75% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 30% |
| Student > Master | 3 | 15% |
| Other | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 4 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 40% |
| Immunology and Microbiology | 4 | 20% |
| Agricultural and Biological Sciences | 2 | 10% |
| Business, Management and Accounting | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 20% |