Profile hidden Markov models for the detection of viruses within metagenomic sequence data.

ABSTRACT: Rapid, sensitive, and specific virus detection is an important component of clinical diagnostics. Massively parallel sequencing enables new diagnostic opportunities that complement traditional serological and PCR based techniques. While massively parallel sequencing promises the benefits of being more comprehensive and less biased than traditional approaches, it presents new analytical challenges, especially with respect to detection of pathogen sequences in metagenomic contexts. To a first approximation, the initial detection of viruses can be achieved simply through alignment of sequence reads or assembled contigs to a reference database of pathogen genomes with tools such as BLAST. However, recognition of highly divergent viral sequences is problematic, and may be further complicated by

SUBMITTER: Skewes-Cox P 

PROVIDER: S-EPMC4139300 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature