VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets.

VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets.
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DOI:
10.1261/rna.079747.123
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发表时间:
2023-12-18
期刊:
RNA (New York, N.Y.)
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在病毒复制过程中,携带RNA基因组的病毒产生非标准病毒基因组(NsVGs),包括复制回写病毒基因组(CbVGs)和缺失型病毒基因组(DelVGs),它们在调节病毒复制和致病过程中发挥着至关重要的作用。由于nsVGs在决定RNA病毒感染结果中的关键作用,近年来对nsVGs的研究蓬勃发展,暴露了对生物信息学工具的需求,这些工具可以在从受感染样本获得的下一代测序数据中准确地识别它们。在这里,我们介绍了我们的数据分析流水线,病毒开源DVG密钥算法2(VODKA2),它被优化为运行在并行计算环境中,用于快速准确地从大数据集中检测NSVG。
During viral replication, viruses carrying an RNA genome produce non-standard viral genomes (nsVGs), including copy-back viral genomes (cbVGs) and deletion viral genomes (delVGs), that play a crucial role in regulating viral replication and pathogenesis. Because of their critical roles in determining the outcome of RNA virus infections, the study of nsVGs has flourished in recent years, exposing a need for bioinformatic tools that can accurately identify them within next-generation sequencing data obtained from infected samples. Here, we present our data analysis pipeline, Viral Opensource DVG Key Algorithm 2 (VODKA2), that is optimized to run on a parallel computing environment for fast and accurate detection of nsVGs from large data sets.
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