High-throughput sequencing for microRNA (miRNA) profiling has revealed a vast complexity of miRNA processing variants, but these are difficult to discern for those without bioinformatics expertise and large computing capability. I previously developed a software solution  (miRspring : miRNA Sequence Profiling; http://mirspring.victorchang.edu.au), that creates a small portable research document that visualizes, calculates and reports on the complexities of miRNA processing for individual data sets. The miRspring document is a javascript HTML document that utilises an index-compression algorithm that allows the reproduction of a complete miRNA sequence data set while retaining a small file size (typically <3 MB). MiRspring documents are an ideal solution to analyse a small number of data sets and are a rich resource to include as supplementary information at the time of publication. A limitation of the miRspring document is the lack of functionality to compare between multiple data sets. At this meeting I will present a new miRspring bioinformatics resource, the miRspring toolkit, a method to analyse large number of miRNA data sets. The miRspring toolkit is built using the R statistical programming language and provides functionality to perform large scale analysis, on standard desktop/laptop hardware configurations. Data can be imported via miRspring documents or aligned BAM files. Analysis tools allow calculation of differential expression, differential 5’ or 3’ isomiR processing, miRNA length analysis, as well as miRNA cluster analysis. Data can be normalized via different methods and downstream analysis can be presented as heat maps, volcano plots, or principle component analysis. I anticipate that the miRspring document along with the miRspring toolkit will be a highly useful research tool that will enhance the analysis of miRNA data sets, provide greater transparency for the community and ultimately increase our understanding of miRNA biology.