PT  - JOURNAL ARTICLE
AU  - Bradley, Thomas
AU  - Moxon, Simon
TI  - FilTar: Using RNA-Seq data to improve microRNA target prediction accuracy in animals
AID  - 10.1101/595322
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 595322
4099  - http://biorxiv.org/content/early/2019/04/01/595322.short
4100  - http://biorxiv.org/content/early/2019/04/01/595322.full
AB  - 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.