Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that are involved in post-transcriptional regulation of gene expression. In this high-throughput sequencing era, a tremendous amount of RNA-seq data is accumulating, and full utilization of publicly available miRNA data is an important challenge. These data are useful to determine expression values for each miRNA, but quantification pipelines are in a primitive stage and still evolving; there are many factors that affect expression values significantly.
Results: We used 304 high-quality microRNA sequencing (miRNA-seq) datasets from NCBI-SRA and calculated expression profiles for different tissues and cell-lines. In each miRNA-seq dataset, we found an average of more than 500 miRNAs with higher than 5x coverage, and we explored the top five highly expressed miRNAs in each tissue and cell-line. This user-friendly miRmine database has options to retrieve expression profiles of single or multiple miRNAs for a specific tissue or cell-line, either normal or with disease information. Results can be displayed in multiple interactive, graphical and downloadable formats.
Availability and implementation: http://guanlab.ccmb.med.umich.edu/mirmine.
Supplementary information: Supplementary data are available at Bioinformatics online.
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