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

Plant microRNA prediction tools that utilize small RNA sequencing data are emerging quickly. These existing tools have at least one of the following problems:

  1. high false positive rate;
  2. long running time;
  3. work only for genomes in their databases;
  4. hard to install or use.

Researchers from Michigan State University develop miR-PREFeR (miRNA PREdiction From small RNA-Seq data), which utilizes 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. They tested miR-PREFeR on several plant species. The results show that miR-PREFeR is sensitive, accurate, fast, and has low memory footprint.

rna-seq

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

CONTACT: yannisun@msu.edu

Lei J, Sun Y. (2104) miR-PREFeR: an accurate, fast, and easy-to-use plant miRNA prediction tool using small RNA-Seq data. Bioinformatics [Epub ahead of print]. [abstract]