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ACValidator: A novel assembly-based approach for in silico verification of circular RNAs

机译:ACValidator:一种基于组装的基于组装的方法,用于圆形RNA的硅验证

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Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons "back-splice" to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs. To this end, we developed Assembly based CircRNA Validator (ACValidator) for in silico verification of circRNAs. ACValidator extracts reads from a user-defined window on either side of a circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the back-spliced junction. When evaluated on simulated datasets, ACValidator achieved over 80% sensitivity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher verification percentages for samples treated with ribonuclease R compared to nontreated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for prioritizing experimental validations. All workflow scripts are freely accessible on our GitHub page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator.
机译:圆形RNA(CircRNA)是进化的保守RNA物种,当彼此外显“背裂”时形成。目前的计算算法检测这些背拼接结产生发散结果,因此需要一种方法来区分真正的Circrna。为此,我们开发了基于集合Circrna验证器(ACValidator)的CircRNA的Silico验证。 ACValidator从Circrna结处的两侧的用户定义窗口中提取读取,并组装它们以生成contigs。这些Contigs与CircrNA序列对齐,以找到跨越背部剪接结的Contig。在对模拟数据集进行评估时,ACValidator在数据集中实现了超过80%的灵敏度,平均为10个CircrNA支持读数,并且具有至少100bp的读取长度。在实验数据集中,与非生成样品相比,ACValidator产生了用核糖核酸酶R处理的样品的验证百分比。我们的工作流程适用于非多层选择的RNASEQ数据集,也可用作优先考虑实验验证的候选选择策略。所有工作流脚本都可以在我们的GitHub页面https://github.com/tgen/acvalidator上自由访问,以及设置和运行ACValidator的详细说明。

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