| Chapter title |
Whole-Genome Shotgun Sequence CNV Detection Using Read Depth
|
|---|---|
| Chapter number | 4 |
| Book title |
Copy Number Variants
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-8666-8_4 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-8665-1, 978-1-4939-8666-8
|
| Authors |
Fatma Kahveci, Can Alkan, Kahveci, Fatma, Alkan, Can |
| Abstract |
With the developments in high-throughput sequencing (HTS) technologies, researchers have gained a powerful tool to identify structural variants (SVs) in genomes with substantially less cost than before. SVs can be broadly classified into two main categories: balanced rearrangements and copy number variations (CNVs). Many algorithms have been developed to characterize CNVs using HTS data, with focus on different types and size range of variants using different read signatures. Read depth (RD) based tools are more common in characterizing large (>10 kb) CNVs since RD strategy does not rely on the fragment size and read length, which are limiting factors in read pair and split read analysis. Here we provide a guideline for a user friendly tool for detecting large segmental duplications and deletions that can also predict integer copy numbers for duplicated genes. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 33% |
| Professor | 1 | 11% |
| Other | 1 | 11% |
| Student > Master | 1 | 11% |
| Unknown | 3 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 22% |
| Computer Science | 2 | 22% |
| Agricultural and Biological Sciences | 1 | 11% |
| Social Sciences | 1 | 11% |
| Unknown | 3 | 33% |