Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
RNA. 2023 Dec 18;30(1):16-25. doi: 10.1261/rna.079747.123.
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.
在病毒复制过程中，携带 RNA 基因组的病毒会产生非标准病毒基因组（nsVGs），包括反向互补病毒基因组（cbVGs）和缺失病毒基因组（delVGs），它们在调节病毒复制和发病机制方面起着至关重要的作用。由于它们在决定 RNA 病毒感染结果方面的关键作用，近年来对 nsVGs 的研究蓬勃发展，这需要能够在从感染样本中获得的下一代测序数据中准确识别它们的生物信息学工具。在这里，我们展示了我们的数据分析管道，即病毒开源 DVG 关键算法 2（VODKA2），它经过优化可在并行计算环境中运行，以便从大数据集中快速准确地检测 nsVGs。
