Name
Title | ||
|---|---|---|
An evaluation of copy number variation detection tools for cancer using whole exome sequencing data. |
Abstract | ||
|---|---|---|
The limited performance of the current CNV detection tools for WES data in cancer indicates the need for developing more efficient and precise CNV detection methods. Due to the complexity of tumors and high level of noise and biases in WES data, employing advanced novel segmentation, normalization and de-noising techniques that are designed specifically for cancer data is necessary. Also, CNV detection development suffers from the lack of a gold standard for performance evaluation. Finally, developing tools with user-friendly user interfaces and visualization features can enhance CNV studies for a broader range of users. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12859-017-1705-x | BMC Bioinformatics |
Keywords | Field | DocType |
Cancer,Copy number variation,Somatic aberrations,Whole-exome sequencing | False discovery rate,Biology,Copy-number variation,Genomics,Whole genome sequencing,Bioinformatics,Genetics,Exome sequencing,Cancer,DNA microarray | Journal |
Volume | Issue | ISSN |
18 | 1 | 1471-2105 |
Citations | PageRank | References |
4 | 0.47 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatima Zare | 1 | 4 | 0.81 |
| Michelle Dow | 2 | 4 | 0.81 |
| Nicholas Monteleone | 3 | 4 | 0.47 |
| Abdelrahman Hosny | 4 | 4 | 0.81 |
| Sheida Nabavi | 5 | 18 | 8.68 |