Bioinformatics for Viral MetagenomicsDavit Bzhalava and Joakim Dillner*
Departments of Laboratory Medicine, Medical Epidemiology & Biostatistics, Karolinska Institutet and Department of Pathology, Karolinska Hospital, Stockholm, Sweden
- *Corresponding Author:
- Joakim Dillner
Department of Laboratory Medicine
Huddinge campus F56, Stockholm, Sweden
E-mail: [email protected]
Received date: May 20, 2013; Accepted date: July 22, 2013; Published date: July 29, 2013
Citation: Bzhalava D, Dillner J (2013) Bioinformatics for Viral Metagenomics. J Data Mining Genomics Proteomics 4:134. doi:10.4172/2153-0602.1000134
Copyright: © 2013 Bzhalava D, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Detection of the presence of known and unknown viruses in biospecimens is today routinely performed using viral metagenomics. Because the sequencing speed and cost per base is rapidly declining with new next generation sequencing technologies, such as HiSeq (Illumina), 454 GS FLX (Roche), SOLiD (ABI) and Ion Torrent Proton (Life Technologies), the bioinformatics analysis is today a most important and increasingly demanding part of viral metagenomics analysis. In this review, we highlight some of the major challenges and the most commonly adapted bioinformatics tools for viral metagenomics.