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Mendeley readers
| Chapter title |
NGS for Sequence Variants.
|
|---|---|
| Chapter number | 1 |
| Book title |
Translational Biomedical Informatics
|
| Published in |
Advances in experimental medicine and biology, November 2016
|
| DOI | 10.1007/978-981-10-1503-8_1 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-101502-1, 978-9-81-101503-8
|
| Authors |
Shaolei Teng |
| Editors |
Bairong Shen, Haixu Tang, Xiaoqian Jiang |
| Abstract |
Recent technological advances in next-generation sequencing (NGS) provide unprecedented power to sequence personal genomes, characterize genomic landscapes, and detect a large number of sequence variants. The discovery of disease-causing variants in patients' genomes has dramatically changed our perspective on precision medicine. This chapter provides an overview of sequence variant detection and analysis in NGS study. We outline the general methods for identifying different types of sequence variants from NGS data. We summarize the common approaches for analyzing and visualizing casual variants associated with complex diseases on precision medicine informatics. |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 25% |
| Researcher | 4 | 20% |
| Student > Ph. D. Student | 4 | 20% |
| Professor > Associate Professor | 2 | 10% |
| Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 3 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 20% |
| Medicine and Dentistry | 4 | 20% |
| Computer Science | 3 | 15% |
| Agricultural and Biological Sciences | 2 | 10% |
| Psychology | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 5 | 25% |