FastViFi: Fast and accurate detection of (Hybrid) Viral DNA and RNA.
FastViFi: Fast and accurate detection of (Hybrid) Viral DNA and RNA.
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DOI：
10.1093/nargab/lqac032
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发表时间：
2022-06
影响因子：
4.6
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中科院分区：
文献类型：
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DNA病毒是已知可介导大量人类疾病（包括癌症）的重要传染源。病毒整合到宿主基因组中以及杂合转录本的形成也与致病性增加有关。然而，病毒基因组的高度变异性需要使用敏感的整体隐马尔可夫模型，这增加了计算复杂性，每个样本通常需要 > 40 个 CPU 小时。在这里，我们描述 FastViFi，一种快速的两级滤波方法，可以减少计算负担。在模拟和癌症基因组数据上，FastViFi 将运行时间提高了 2 个数量级，并且在具有挑战性的数据集上具有相当的准确性。最近发表的方法主要集中于使用局部组装来识别病毒整合到人类宿主基因组中的位置，但没有扩展到 RNA。为了识别人类病毒杂交转录本，我们还开发了 Epstein Barr 病毒 (EBV) 的整体隐马尔可夫模型，将其添加到乙型肝炎 (HBV)、丙型肝炎 (HCV) 病毒和人乳头瘤病毒 (HPV) 模型中，并使用 FastViFi 查询胃癌 (EBV) 和肝癌 (HBV/HCV) 的 RNA-seq 数据。 FastViFi 每个样本的运行时间不到 10 分钟，并鉴定出多种融合病毒和人类基因的杂交体，这表明了肿瘤病毒致病性的新机制。 FastViFi 可从 https://github.com/sara-javadzadeh/FastViFi 获取。
DNA viruses are important infectious agents known to mediate a large number of human diseases, including cancer. Viral integration into the host genome and the formation of hybrid transcripts are also associated with increased pathogenicity. The high variability of viral genomes, however requires the use of sensitive ensemble hidden Markov models that add to the computational complexity, often requiring > 40 CPU-hours per sample. Here, we describe FastViFi, a fast 2-stage filtering method that reduces the computational burden. On simulated and cancer genomic data, FastViFi improved the running time by 2 orders of magnitude with comparable accuracy on challenging data sets. Recently published methods have focused on identification of location of viral integration into the human host genome using local assembly, but do not extend to RNA. To identify human viral hybrid transcripts, we additionally developed ensemble Hidden Markov Models for the Epstein Barr virus (EBV) to add to the models for Hepatitis B (HBV), Hepatitis C (HCV) viruses and the Human Papillomavirus (HPV), and used FastViFi to query RNA-seq data from Gastric cancer (EBV) and liver cancer (HBV/HCV). FastViFi ran in <10 minutes per sample and identified multiple hybrids that fuse viral and human genes suggesting new mechanisms for oncoviral pathogenicity. FastViFi is available at https://github.com/sara-javadzadeh/FastViFi.