Bioinformatic Analyses of Whole-Genome Sequence Data in a Public Health Laboratory
| Autor: | Kelly F. Oakeson, Jennifer Marie Wagner, Michelle Mendenhall, Andreas Rohrwasser, Robyn Atkinson-Dunn |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Emerging Infectious Diseases, Vol 23, Iss 9, Pp 1441-1445 (2017) |
| Druh dokumentu: | article |
| ISSN: | 1080-6040 1080-6059 |
| DOI: | 10.3201/eid2309.170416 |
| Popis: | The ability to generate high-quality sequence data in a public health laboratory enables the identification of pathogenic strains, the determination of relatedness among outbreak strains, and the analysis of genetic information regarding virulence and antimicrobial-resistance genes. However, the analysis of whole-genome sequence data depends on bioinformatic analysis tools and processes. Many public health laboratories do not have the bioinformatic capabilities to analyze the data generated from sequencing and therefore are unable to take full advantage of the power of whole-genome sequencing. The goal of this perspective is to provide a guide for laboratories to understand the bioinformatic analyses that are needed to interpret whole-genome sequence data and how these in silico analyses can be implemented in a public health laboratory setting easily, affordably, and, in some cases, without the need for intensive computing resources and infrastructure. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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