title: miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Biology, University of Virginia, Charlottesville, VA 22904, USA.
authors.forename: Xiaozeng
authors.initials: X
authors.lastname: Yang
authors.forename: Lei
authors.initials: L
authors.lastname: Li
mesh_terms: D057225:Data Mining / Q000379:methods*; D015870:Gene Expression; D035683:MicroRNAs / Q000235:genetics*; D008957:Models, Genetic; D010944:Plants / Q000235:genetics*; D012984:Software; D059467:Transcriptome
chemical_list: D035683:MicroRNAs