TY - JOUR T1 - SeroBA: rapid high-throughput serotyping of Streptococcus pneumoniae from whole genome sequence data AU - Epping, Lennard AU - van Tonder, Andries J. AU - Gladstone, Rebecca A. AU - The Global Pneumococcal Sequencing Consortium AU - Bentley, Stephen D. AU - Page, Andrew J. AU - Keane, Jacqueline A. AB - Streptococcus pneumoniae is responsible for 240 000–460 000 deaths in children under 5 years of age each year. Accurate identification of pneumococcal serotypes is important for tracking the distribution and evolution of serotypes following the introduction of effective vaccines. Recent efforts have been made to infer serotypes directly from genomic data but current software approaches are limited and do not scale well. Here, we introduce a novel method, SeroBA, which uses a k-mer approach. We compare SeroBA against real and simulated data and present results on the concordance and computational performance against a validation dataset, the robustness and scalability when analysing a large dataset, and the impact of varying the depth of coverage on sequence-based serotyping. SeroBA can predict serotypes, by identifying the cps locus, directly from raw whole genome sequencing read data with 98 % concordance using a k-mer-based method, can process 10 000 samples in just over 1 day using a standard server and can call serotypes at a coverage as low as 15–21×. SeroBA is implemented in Python3 and is freely available under an open source GPLv3 licence from: https://github.com/sanger-pathogens/seroba KW - Streptococcus pneumoniae KW - serotyping KW - pneumococcal KW - whole genome sequencing KW - k-mer method KW - 610 Medizin und Gesundheit PY - 2018 LA - eng PB - Robert Koch-Institut JO - MICROBIAL GENOMICS VL - 4 IS - 7 SP - 1 EP - 6 DO - 10.1099/mgen.0.000186 ER -