Hallgren Malte B, Overballe-Petersen Søren, Lund Ole, Hasman Henrik, Clausen Philip T L C
National Food Institute, Technical University of Denmark, Kemitorvet 204, 2800 Kgs. Lyngby, Denmark.
Department of Bacteria, Parasites and Fungi, Statens Serum Institut, 2300 Copenhagen, Denmark.
Biol Methods Protoc. 2021 Apr 21;6(1):bpab008. doi: 10.1093/biomethods/bpab008. eCollection 2021.
For detection of clonal outbreaks in clinical settings, we present a complete pipeline that generates a single-nucleotide polymorphisms-distance matrix from a set of sequencing reads. Importantly, the program is able to handle a separate mix of both short reads from the Illumina sequencing platforms and long reads from Oxford Nanopore Technologies' (ONT) platforms as input. MINTyper performs automated reference identification, alignment, alignment trimming, optional methylation masking, and pairwise distance calculations. With this approach, we could rapidly and accurately cluster a set of DNA sequenced isolates, with a known epidemiological relationship to confirm the clustering. Functions were built to allow for both high-accuracy methylation-aware base-called MinION reads (hac_m Q10) and fast generated lower-quality reads (fast Q8) to be used, also in combination with Illumina data. With fast Q8 reads a higher number of base pairs were excluded from the calculated distance matrix, compared with the high-accuracy methylation-aware Q10 base-calling of ONT data. Nonetheless, when using different qualities of ONT data with corresponding input parameters, the clustering of isolates were nearly identical.
为了在临床环境中检测克隆爆发，我们提出了一个完整的流程，该流程可从一组测序读数生成单核苷酸多态性距离矩阵。重要的是，该程序能够处理来自Illumina测序平台的短读数和来自牛津纳米孔技术公司（ONT）平台的长读数的单独混合作为输入。MINTyper执行自动参考识别、比对、比对修剪、可选的甲基化屏蔽和成对距离计算。通过这种方法，我们可以快速准确地对一组具有已知流行病学关系的DNA测序分离株进行聚类，以确认聚类情况。构建的功能允许使用高精度的甲基化感知碱基识别的MinION读数（hac_m Q10）和快速生成的低质量读数（fast Q8），也可与Illumina数据结合使用。与ONT数据的高精度甲基化感知Q10碱基识别相比，使用fast Q8读数时，计算出的距离矩阵中排除了更多的碱基对。尽管如此，当使用具有相应输入参数的不同质量的ONT数据时，分离株的聚类几乎相同。
