The main idea behind isomiR-SEA is to provide users with an integrated and user-friendly tool capable to extract miRNAs expression levels from high-throughput sequencing data ensuring high degrees of accuracy and detail.
The innovation introduced by isomiR-SEA consists in the pragmatic approach implemented to detect and quantify miRNAs into the analysed samples. Indeed the tool identifies as reads accounting for miRNAs all the sequences that retain specific miRNAs features and that, as a consequence, can interact in some way with mRNA target molecules.
Clearly these interactions strictly depend on the amount and kind of differences detected in the read with respect to the miRNA from which it derives. Furthermore, specific miRNA positions are nowadays considered fundamental to guarantee miRNA:mRNA target interaction, as proven in several researches conducted in the last decade and exploited in most of the miRNAs target predicion algorithms.
In the light of these considerations and given the lack of software tools capable to take into account thses miRNAs features during the reads alignment phase, we have developed isomiR-SEA.
isomiR-SEA is the first tool implemented in order to perform reads alignment on miRNAs databases by considering the miRNA:mRNA interaction pairing aspects. This novelty allows isomiR-SEA to reach high accuracy in miRNAs expression levels extraction and at the same time to provide users with a very detailed description of the detected expression profiles.
In other words, why biologists have to look pictures from 0.5 Megapixel cameras when the available knowledge allows them to look at the same images from 10 Megapixel cameras? Additionally it is usually simpler reduce the degree of detail of a pitcure than increase it thus isomiR-SEA has been implemented in order to provide users with the most complete and detailed information that can be extracted from data.
This precise representation, made possible by an accurate and fast alignment procedure, includes the mature miRNAs and miRNA isoforms detected in the sample and their possible mode of interaction with a target mRNA. The obtained information can be freely managed by users in order to highlight those aspects considered as more meaningful.