Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, Saarland University researchers developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, they now present miRMaster 2 with a wide range of updates and new features. The researchers extended their reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). They also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, they incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, the researchers integrated differential expression analysis with the miRNA enrichment analysis tool miEAA.
Availability – miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2.