General Information
| Description | An accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data |
| Homepage | https://github.com/hangelwen/miR-PREFeR |
Publications
miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data
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
Contact:
yannisun@msu.edu
Supplementary information:
Supplementary data are available at Bioinformatics online.
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