FilTar: Using RNA-Seq data to improve microRNA target prediction accuracy in animals

Abstract

MicroRNAs (miRNAs) are a class of small non-coding RNA molecule, approximately 22nt in length, which guide the repression of mRNA transcripts. A number of tools have been developed to predict miRNA targets in animals which do not account for the effects of a specific cellular context on miRNA targeting. We present FilTar (Filtering of predicted miRNA Targets), a method which utilises available RNA-Seq information to filter non-or lowly expressed transcripts and refine existing 3'UTR annotations for a given cellular context, to increase miRNA target prediction accuracy in animals.The FilTar tool is available at https://github.com/TBradley27/FilTar.