TheViral MetaGenome Annotation Pipeline(VMGAP):an automated tool for the functional annotation of viral Metagenomic shotgun sequencing data
| Autor: | Hernan Lorenzi, Jeff Hoover, Leonid Kagan, Jason M. Inman, Todd Safford, Shannon J. Williamson, Sean D. Murphy |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
0303 health sciences
030306 microbiology Shotgun sequencing metagenomic annotation Enzyme Commission number Biology computer.software_genre Data type Genome Pipeline (software) 03 medical and health sciences Annotation Protein sequencing Metagenomics Genetics J. Craig Venter Institute Standard Operating Procedures Data mining viral annotation computer 030304 developmental biology |
| Zdroj: | Standards in Genomic Sciences |
| ISSN: | 1944-3277 |
| Popis: | In the past few years, the field of metagenomics has been growing at an accelerated pace, particularly in response to advancements in new sequencing technologies. The large volume of sequence data from novel organisms generated by metagenomic projects has triggered the development of specialized databases and tools focused on particular groups of organisms or data types. Here we describe a pipeline for the functional annotation of viral metagenomic sequence data. The Viral MetaGenome Annotation Pipeline (VMGAP) pipeline takes advantage of a number of specialized databases, such as collections of mobile genetic elements and environmental metagenomes to improve the classification and functional prediction of viral gene products. The pipeline assigns a functional term to each predicted protein sequence following a suite of comprehensive analyses whose results are ranked according to a priority rules hierarchy. Additional annotation is provided in the form of enzyme commission (EC) numbers, GO/MeGO terms and Hidden Markov Models together with supporting evidence. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink