SMiRK

Micro RNAs (miRNAs), important regulators of cell function, can be interrogated by high-throughput sequencing in a rapid and cost-effective manner. However, the tremendous amount of data generated by such methods is not easily analyzed. In order to extract meaningful information and draw biological conclusions from miRNA data, many challenges in quality control, alignment, normalization, and analysis must be overcome. Typically, these would only be possible with the dedicated efforts of a specialized computational biologist for a sustained period of time.
Here, we present SMiRK, an automated pipeline that allows such tasks to be completed with minimal time and without dedicated bioinformatics personnel. SMiRK's flexibility also allows experienced users to exert more control, if they wish. We describe how SMiRK automatically normalizes the data, removes low-information miRNAs, and produces heatmaps of the processed data. We give details on SMiRK's implementation and use cases for novice and advanced users. As a demonstration of its capabilities, SMiRK was used to rapidly and automatically analyze a dataset taken from the literature.
SMiRK is a useful and efficient tool that can be used by investigators at multiple skill levels. Those who lack bioinformatics training can use it to easily and automatically analyze their data, while those with experience will find it beneficial to not need to write tools from scratch.[1]

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