AYUKA: A toolkit for fast viral genotyping using whole genome sequencing

Abstract Technological advances enabled the frequent use of whole genome sequencing in the clinical microbiology laboratory. While generating data is now easier than ever, the computational resources and expertise required for analysis are still a challenge for clinical applications. Since it is not always possible to collect clinical specimens at the peak viral load, sequencing results are also not always amenable for analysis with bioinformatics pipelines that always require high quality data. Here we present a fast and reliable method, we named AYUKA, for analysis of viral sequencing data that does not require data pre-processing and provides quality control metrics including estimates for sequencing depth and genome coverage, as well as identifying the viral genotypes in a sample and distinguishing mixed infection from recombinants. This method can be applied to any virus where a classification by genotype is employed and determining it is relevant. We generated a validation dataset composed of cultured and sequenced reference adenoviruses from distinct species, that we compared with the gold standard clinical processing pipeline currently implemented to demonstrate reliability. The validation shows better sensitivity than mapping and perfect specificity in detecting the correct genotypes and in a wide range of adenovirus species. Run time was consistently under one minute per sample on a standard laptop, allowing the analysis of more than 100 samples per hour. This open-source method is available at https://github.com/afonsoguerra/AYUKA and precomputed databases are available at https://zenodo.org/record/6521576 allowing analysis of raw data straight from the sequencer within minutes on a standard computer, with minimum setup or expertise required to perform the analysis. The information contained within the AYUKA report can be of use for both the clinical team that collected the sample, but also for guiding the bioinformatics analysis team in the in-depth downstream analyses and genetic epidemiology investigations.