simulated Reads

<i>Streptococcus pneumoniae</i> is responsible for nearly 1 million deaths every year worldwide. To target the most dominant serotypes with vaccines it is import to track the distribution and evolution of serotypes within the population. Recent efforts have been made to infer serotypes directly from genomic data. Current software approaches are limited and do not scale well. We introduce a novel method SeroBA which uses a hybrid assembly and mapping approach. We have compared SeroBA against real and simulated data.<br>

肺炎链球菌（Streptococcus pneumoniae）每年在全球范围内造成近百万例死亡。为通过疫苗靶向最具优势的血清型（serotypes），追踪人群内血清型的分布与演化进程至关重要。近年来已有多项研究尝试直接从基因组数据（genomic data）中推断血清型，但现有软件方法仍存在诸多局限，且难以实现规模化应用。本研究提出一种名为SeroBA的新型方法，该方法采用混合组装与序列映射（mapping）的分析策略。我们已将SeroBA与真实及模拟数据集开展对比验证实验。