miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants
miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants
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DOI：
10.1093/bioinformatics/btr430
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发表时间：
2011-09-15
期刊：
影响因子：
5.8
通讯作者：
Li, Lei
中科院分区：
文献类型：
--
作者：
Yang, Xiaozeng;Li, Lei
动机：通过新一代测序对小 RNA 文库进行超深度采样，提供了有关各种植物物种的 microRNA (miRNA) 转录组的丰富信息。然而，几乎没有开发出计算工具来有效地对复杂信息进行解卷积。结果：我们试图利用沿着 miRNA 前体的小 RNA 读数的特征分布作为植物中的模型来分析已知 miRNA 基因的表达并识别新的基因。一个免费的软件包 miRDeep-P 是通过修改 miRDeep 开发的，它基于动物 miRNA 生物发生的概率模型，具有植物特异性的评分系统和过滤标准。我们在来自三种植物的八个小 RNA 文库上测试了 miRDeep-P。我们的结果证明 miRDeep-P 是一种有效且易于使用的工具，用于表征植物中的 miRNA 转录组。
Motivation: Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information.Results: We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants.