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Bioinformatics. 2014 Oct;30(19):2837-9. doi: 10.1093/bioinformatics/btu380. Epub 2014 Jun 14.

miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data.

Author information

1
Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.

Abstract

SUMMARY:

Plant microRNA prediction tools that use small RNA-sequencing data are emerging quickly. These existing tools have at least one of the following problems: (i) high false-positive rate; (ii) long running time; (iii) work only for genomes in their databases; (iv) hard to install or use. We developed miR-PREFeR (miRNA PREdiction From small RNA-Seq data), which uses expression patterns of miRNA and follows the criteria for plant microRNA annotation to accurately predict plant miRNAs from one or more small RNA-Seq data samples of the same species. We tested miR-PREFeR on several plant species. The results show that miR-PREFeR is sensitive, accurate, fast and has low-memory footprint.

AVAILABILITY AND IMPLEMENTATION:

https://github.com/hangelwen/miR-PREFeR

PMID:
24930140
DOI:
10.1093/bioinformatics/btu380
[Indexed for MEDLINE]

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