Name
Abstract | ||
|---|---|---|
Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1211-6 | BMC Bioinformatics |
Keywords | Field | DocType |
Big data,Cloud AWS,Ensemble calling,Joint calling,SNV,Scalable,Supercomputer,Variant calling,WGS | Data science,Supercomputer,Computer science,Genomics,Genome human,Bioinformatics,Big data,Scalability,Cloud computing | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.38 | 11 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhuoyi Huang | 1 | 1 | 0.38 |
| Navin Rustagi | 2 | 23 | 1.91 |
| Narayanan Veeraraghavan | 3 | 24 | 2.53 |
| Andrew Carroll | 4 | 1 | 1.05 |
| Richard A. Gibbs | 5 | 56 | 10.04 |
| Eric Boerwinkle | 6 | 54 | 7.60 |
| Manjunath Gorentla Venkata | 7 | 86 | 20.02 |
| Fuli Yu | 8 | 2 | 0.74 |