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Oxford Screening CSF and Respiratory samples (‘OSCAR’): results of a pilot study to screen clinical samples from a diagnostic microbiology laboratory for viruses using Illumina next generation sequencing.

Oxford Screening CSF and Respiratory samples (‘OSCAR’): results of a pilot study to screen clinical samples from a diagnostic microbiology laboratory for viruses using Illumina next generation sequencing.
Author Information (click to view)

Sharp C, Golubchik T, Gregory WF, McNaughton AL, Gow N, Selvaratnam M, Mirea A, Foster D, Andersson M, Klenerman P, Jeffery K, Matthews PC,


Sharp C, Golubchik T, Gregory WF, McNaughton AL, Gow N, Selvaratnam M, Mirea A, Foster D, Andersson M, Klenerman P, Jeffery K, Matthews PC, (click to view)

Sharp C, Golubchik T, Gregory WF, McNaughton AL, Gow N, Selvaratnam M, Mirea A, Foster D, Andersson M, Klenerman P, Jeffery K, Matthews PC,

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BMC research notes 2018 02 0911(1) 120 doi 10.1186/s13104-018-3234-8
Abstract
OBJECTIVES
There is increasing interest in the use of metagenomic (next generation sequencing, NGS) approaches for diagnosis of infection. We undertook a pilot study to screen samples submitted to a diagnostic microbiology laboratory in a UK teaching hospital using Illumina HiSeq. In the short-term, this small dataset provides insights into the virome of human respiratory and cerebrospinal fluid (CSF) samples. In the longer term, assimilating metagenomic data sets of this nature can inform optimization of laboratory and bioinformatic methods, and develop foundations for the interpretation of results in a clinical context. The project underpins a larger ongoing effort to develop NGS pipelines for diagnostic use.

DATA DESCRIPTION
Our data comprise a complete metagenomic dataset from 20 independent samples (10 CSF and 10 respiratory) submitted to the clinical microbiology laboratory for a large UK teaching hospital (Oxford University Hospitals NHS Foundation Trust). Sequences have been uploaded to the European Nucleotide Archive and are also presented as Krona plots through which the data can be interactively visualized. In the longer term, further optimization is required to better define sensitivity and specificity of this approach to clinical samples.

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