Runs of Homozygosity (RoHs) are popular among geneticists as the footprint of demographic processes, evolutionary forces and inbreeding in shaping our genome, and are known to confer risk of Mendelian and complex diseases. Notwithstanding growing interest in their study, there is unmet need for reliable and rapid methods for genomic analyses in large data sets. AUDACITY is a tool integrating novel RoH detection algorithm and autozygosity prediction score for prioritization of mutation-surrounding regions. It processes data in VCF file format, and outperforms existing methods in identifying RoHs of any size. Simulations and analysis of real exomes/genomes show its potential to foster future RoH studies in medical and population genomics.

纯合子（RoHs）的运行在遗传学家中非常普遍，因为它在人口统计学，进化力和近亲繁殖方面影响着我们的基因组，并且已知会带来孟德尔和复杂疾病的风险。尽管对他们的研究兴趣日益增长，但仍未满足对可靠和快速的大数据集基因组分析方法的需求。AUDACITY是一种工具，它结合了新颖的RoH检测算法和自动纯合度预测得分，可对突变周围区域进行优先级排序。它以VCF文件格式处理数据，并且在识别任何大小的RoH方面优于现有方法。实际外显子组/基因组的仿真和分析显示出其潜在的潜力，可促进未来在医学和人群基因组学中的RoH研究。