FlaiMapper

Recent discoveries show that most types of small non-coding RNAs (sncRNAs) such as miRNAs, snoRNAs and tRNAs get further processed into putatively active smaller RNA species. Their roles, genetic profiles and underlying processing mechanisms are only partially understood. To find their quantities and characteristics, a proper annotation is essential. Here, we present FlaiMapper, a method that extracts and annotates the locations of sncRNA-derived RNAs (sncdRNAs). These sncdRNAs are often detected in sequencing data and observed as fragments of their precursor sncRNA. Using small RNA-seq read alignments, FlaiMapper is able to annotate fragments primarily by peak detection on the start and end position densities followed by filtering and a reconstruction process.
To assess performance of FlaiMapper, we used independent publicly available small RNA-seq data. We were able to detect fragments representing putative sncdRNAs from nearly all types of sncRNA, including 97.8% of the annotated miRNAs in miRBase that have supporting reads. Comparison of FlaiMapper-predicted boundaries of miRNAs with miRBase entries demonstrated that 89% of the start and 54% of the end positions are identical. Additional benchmarking showed that FlaiMapper is superior in performance compared with existing software. Further analysis indicated a variety of characteristics in the fragments, including sequence motifs and relations with RNA interacting factors. These characteristics set a good basis for further research on sncdRNAs.
The platform independent GPL licensed Python 2.7 code is available at: https://github.com/yhoogstrate/flaimapper.[1]

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