MOTIVATION: Influenza 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. RESULTS: Standard human reference viruses were insufficient for mapping diverse influenza samples in simulation. VAPOR retrieved references for 257 real whole-genome sequencing samples with a mean of >99.8% identity to assemblies, and increased the proportion of mapped reads by up to 13.3% compared to standard references. VAPOR has the potential to improve the robustness of bioinformatics pipelines for surveillance and could be adapted to other RNA viruses. AVAILABILITY AND IMPLEMENTATION: VAPOR is available at https://github.com/connor-lab/vapor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The authors describe a pilot project to standardize local laboratory data at five Indian Health Service (IHS) medical facilities by mapping laboratory test names to Logical Observation Identifier Names and Codes (LOINC). An automated mapping tool was developed to assign LOINC codes. At these sites, they were able to map from 63% to 76% of the local active laboratory tests to LOINC using the mapping tool. Eleven percent to 27% of the tests were mapped manually. They could not assign LOINC codes to 6% to 19% of the laboratory tests due to incomplete or incorrect information about these tests. The results achieved approximate other similar efforts. Mapping of laboratory test names to LOINC codes will allow IHS to aggregate laboratory data more easily for disease surveillance and clinical and administrative reporting efforts. This project may provide a model for standardization efforts in other health systems.