Department of Pathology, Johns Hopkins University SOM, 720 Rutland Avenue/Ross Bldg. Rm 632B, Baltimore, MD, 21205, USA.
BMC Bioinformatics. 2018 Jul 23;19(1):275. doi: 10.1186/s12859-018-2287-y.
miRNAs play important roles in the regulation of gene expression. The rapidly developing field of microRNA sequencing (miRNA-seq; small RNA-seq) needs comprehensive, robust, user-friendly and standardized bioinformatics tools to analyze these large datasets. We present miRge 2.0, in which multiple enhancements were made towards these goals.
miRge 2.0 has become more comprehensive with increased functionality including a novel miRNA detection method, A-to-I editing analysis, integrated standardized GFF3 isomiR reporting, and improved alignment to miRNAs. The novel miRNA detection method uniquely uses both miRNA hairpin sequence structure and composition of isomiRs resulting in higher specificity for potential miRNA identification. Using known miRNA data, our support vector machine (SVM) model predicted miRNAs with an average Matthews correlation coefficient (MCC) of 0.939 over 32 human cell datasets and outperformed miRDeep2 and miRAnalyzer regarding phylogenetic conservation. The A-to-I editing detection strongly correlated with a reference dataset with adjusted R = 0.96. miRge 2.0 is the most up-to-date aligner with custom libraries to both miRBase v22 and MirGeneDB v2.0 for 6 species: human, mouse, rat, fruit fly, nematode and zebrafish; and has a tool to create custom libraries. For user-friendliness, miRge 2.0 is incorporated into bcbio-nextgen and implementable through Bioconda.
miRge 2.0 is a redesigned, leading miRNA RNA-seq aligner with several improvements and novel utilities. miRge 2.0 is freely available at: https://github.com/mhalushka/miRge .
miRNAs 在基因表达调控中发挥着重要作用。快速发展的 microRNA 测序(miRNA-seq;small RNA-seq)领域需要全面、强大、用户友好且标准化的生物信息学工具来分析这些大型数据集。我们介绍 miRge 2.0,它在朝着这些目标发展的过程中进行了多项增强。
miRge 2.0 变得更加全面,功能更加强大,包括一种新的 miRNA 检测方法、A-to-I 编辑分析、集成标准化 GFF3 同型 miRNA 报告,以及对 miRNA 的改进对齐。新的 miRNA 检测方法独特地使用 miRNA 发夹序列结构和同型 miRNA 的组成,从而提高了潜在 miRNA 识别的特异性。使用已知的 miRNA 数据,我们的支持向量机(SVM)模型在 32 个人类细胞数据集上预测 miRNA 的平均马修斯相关系数(MCC)为 0.939,在系统发育保守性方面优于 miRDeep2 和 miRAnalyzer。A-to-I 编辑检测与参考数据集的相关性很强,调整后的 R=0.96。miRge 2.0 是最新的对齐器,具有针对 miRBase v22 和 MirGeneDB v2.0 的定制库,适用于 6 个物种:人类、小鼠、大鼠、果蝇、线虫和斑马鱼;并具有创建自定义库的工具。为了方便用户,miRge 2.0 被整合到 bcbio-nextgen 中,并可通过 Bioconda 实现。
miRge 2.0 是一个经过重新设计的、领先的 miRNA RNA-seq 对齐器,具有多项改进和新颖的实用功能。miRge 2.0 可在以下网址免费获得:https://github.com/mhalushka/miRge 。