Virus

Influenza Classification from Short Reads with VAPOR Facilitates Robust Mapping Pipelines and Zoonotic Strain Detection for Routine Surveillance Applications

14 days ago   |   By Oxford Journals

AbstractMotivationInfluenza viruses represent a global public health burden due to annual epidemics and pandemic potential. Due to a rapidly evolving RNA genome, inter-species transmission, intra-host variation, and noise in short-read data, reads can be lost during mapping, and de novo assembly can be time consuming and result in misassembly. We assessed read loss during mapping, and designed a graph-based classifier, VAPOR, for selecting mapping references, assembly validation, and detection of strains of non-human origin.ResultsStandard human reference viruses were insufficient for...
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