Motivation: Ultra-deep sampling of small RNA libraries by nextgeneration 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. © The Author 2011. Published by Oxford University Press. All rights reserved.
CITATION STYLE
Yang, X., & Li, L. (2011). miRDeep-P: A computational tool for analyzing the microRNA transcriptome in plants. Bioinformatics, 27(18), 2614–2615. https://doi.org/10.1093/bioinformatics/btr430
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