Name
Title | ||
|---|---|---|
gemBS - high throughput processing for DNA methylation data from Bisulfite Sequencing. |
Abstract | ||
|---|---|---|
Motivation DNA methylation is essential for normal embryogenesis and development in mammals and can be captured at single base pair resolution by whole genome bisulfite sequencing (WGBS). Current available analysis tools are becoming rapidly outdated as they lack sensible functionality and efficiency to handle large amounts of data now commonly created. Results We developed gemBS, a fast high-throughput bioinformatics pipeline specifically designed for large scale BS-Seq analysis that combines a high performance BS-mapper (GEM3) and a variant caller specifically for BS-Seq data (BScall). gemBS provides genotype information and methylation estimates for all genomic cytosines in different contexts (CpG and non-CpG) and a set of quality reports for comprehensive and reproducible analysis. gemBS is highly modular and can be easily automated, while producing robust and accurate results. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1093/bioinformatics/bty690 | BIOINFORMATICS |
Field | DocType | Volume |
Computer science,Bisulfite sequencing,DNA methylation,Bioinformatics,Computational biology,Throughput | Journal | 35 |
Issue | ISSN | Citations |
5 | 1367-4803 | 0 |
PageRank | References | Authors |
0.34 | 1 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angelika Merkel | 1 | 19 | 1.78 |
| Marcos Fernández-Callejo | 2 | 0 | 0.34 |
| Eloi Casals | 3 | 0 | 0.34 |
| Santiago Marco-Sola | 4 | 18 | 2.12 |
| Ronald Schuyler | 5 | 0 | 0.34 |
| Ivo G Gut | 6 | 0 | 0.34 |
| Simon Heath | 7 | 6 | 1.00 |