Venus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data.
Venus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data.
复制标题
DOI：
10.1371/journal.pcbi.1010636
复制
发表时间：
2022-10
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
早期和准确地检测临床和环境样本中的病毒对于有效的公共卫生保健，治疗和治疗至关重要。虽然PCR以高灵敏度检测潜在的病原体，但它难以扩展，并且需要了解病原体的确切序列。随着下一代单细胞测序技术的出现，现在可以在尽可能高的分辨率细胞上仔细检查病毒转录组学。这种新发现的研究单个细胞的能力为以前所未有的分辨率了解病毒病理生理学开辟了新的途径。为了利用这种能力，我们提出了一种高效准确的计算管道，名为Venus，用于单细胞和大块组织RNA-seq数据中的病毒检测和整合位点发现。具体来说，Venus解决了两个主要问题：组织/细胞类型是否被病毒或感兴趣的病毒感染？如果被感染，病毒是否以及在哪里插入了人类基因组？我们的分析可以分为两个部分-验证和发现。首先，为了验证，我们将Venus应用于经过充分研究的病毒数据集，例如HBV-肝细胞癌和HIV-抗逆转录病毒治疗感染。其次，为了发现，我们分析了HIV感染的神经系统患者和深度测序的T细胞等数据集。我们在大脑的新靶点和免疫细胞中的高置信度整合位点检测到病毒转录本。总之，在这里，我们描述金星，一个公开可用的软件，我们相信这将是一个有价值的病毒调查工具，为科学界在整个。
Early and accurate detection of viruses in clinical and environmental samples is essential for effective public healthcare, treatment, and therapeutics. While PCR detects potential pathogens with high sensitivity, it is difficult to scale and requires knowledge of the exact sequence of the pathogen. With the advent of next-gen single-cell sequencing, it is now possible to scrutinize viral transcriptomics at the finest possible resolution–cells. This newfound ability to investigate individual cells opens new avenues to understand viral pathophysiology with unprecedented resolution. To leverage this ability, we propose an efficient and accurate computational pipeline, named Venus, for virus detection and integration site discovery in both single-cell and bulk-tissue RNA-seq data. Specifically, Venus addresses two main questions: whether a tissue/cell type is infected by viruses or a virus of interest? And if infected, whether and where has the virus inserted itself into the human genome? Our analysis can be broken into two parts–validation and discovery. Firstly, for validation, we applied Venus on well-studied viral datasets, such as HBV- hepatocellular carcinoma and HIV-infection treated with antiretroviral therapy. Secondly, for discovery, we analyzed datasets such as HIV-infected neurological patients and deeply sequenced T-cells. We detected viral transcripts in the novel target of the brain and high-confidence integration sites in immune cells. In conclusion, here we describe Venus, a publicly available software which we believe will be a valuable virus investigation tool for the scientific community at large.
登录
查看更多内容
DOI：
10.1007/978-1-4939-3572-7_13
发表时间：
2016-01-01
期刊：
DATA MINING TECHNIQUES FOR THE LIFE SCIENCES
影响因子：
--
作者：
Dobin, Alexander;Gingeras, Thomas R.
通讯作者：
Gingeras, Thomas R.
影响因子：
7.3
作者：
Marban C;Forouzanfar F;Ait-Ammar A;Fahmi F;El Mekdad H;Daouad F;Rohr O;Schwartz C
通讯作者：
Schwartz C
影响因子：
5.2
作者：
Kazachenka A;Kassiotis G
通讯作者：
Kassiotis G
影响因子：
16.6
作者：
Zheng GX;Terry JM;Belgrader P;Ryvkin P;Bent ZW;Wilson R;Ziraldo SB;Wheeler TD;McDermott GP;Zhu J;Gregory MT;Shuga J;Montesclaros L;Underwood JG;Masquelier DA;Nishimura SY;Schnall-Levin M;Wyatt PW;Hindson CM;Bharadwaj R;Wong A;Ness KD;Beppu LW;Deeg HJ;McFarland C;Loeb KR;Valente WJ;Ericson NG;Stevens EA;Radich JP;Mikkelsen TS;Hindson BJ;Bielas JH
通讯作者：
Bielas JH
影响因子：
4.9
作者：
Benachenhou F;Sperber GO;Bongcam-Rudloff E;Andersson G;Boeke JD;Blomberg J
通讯作者：
Blomberg J