Name
Title | ||
|---|---|---|
Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers. |
Abstract | ||
|---|---|---|
The choice of well-performing tools for alignment and variant calling is crucial for the correct interpretation of exome sequencing data obtained from mixed samples, and common pipelines are suboptimal. We were able to relate observed substantial differences in performance to the underlying statistical models of the tools, and to pinpoint the error sources of false positive and false negative calls. These findings might inspire new software developments that improve exome sequencing pipelines and further the field of precision cancer treatment. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12859-016-1417-7 | BMC Bioinformatics |
Keywords | Field | DocType |
Cancer genomics,Exome sequencing,SNV,Variant caller integration,Variant calling | Data mining,Data set,Allele frequency,Computer science,Exome,Statistical model,Bioinformatics,Cancer,Exome sequencing | Journal |
Volume | Issue | ISSN |
18 | 1 | 1471-2105 |
Citations | PageRank | References |
6 | 0.93 | 19 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ariane L. Hofmann | 1 | 6 | 0.93 |
| Jonas Behr | 2 | 269 | 27.72 |
| Jochen Singer | 3 | 18 | 2.92 |
| Jack Kuipers | 4 | 7 | 1.96 |
| Christian Beisel | 5 | 6 | 1.27 |
| Peter Schraml | 6 | 6 | 1.27 |
| H Moch | 7 | 131 | 15.90 |
| Niko Beerenwinkel | 8 | 696 | 102.47 |