Panwar Bharat, Omenn Gilbert S, Guan Yuanfang
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Bioinformatics. 2017 May 15;33(10):1554-1560. doi: 10.1093/bioinformatics/btx019.
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.
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.
http://guanlab.ccmb.med.umich.edu/mirmine.
Supplementary data are available at Bioinformatics online.
微小RNA（miRNA）是参与基因表达转录后调控的小型非编码RNA。在这个高通量测序时代，大量的RNA测序（RNA-seq）数据正在积累，充分利用公开可用的miRNA数据是一项重要挑战。这些数据对于确定每个miRNA的表达值很有用，但定量流程尚处于初级阶段且仍在不断发展；有许多因素会显著影响表达值。
我们使用了来自NCBI-SRA的304个高质量微小RNA测序（miRNA-seq）数据集，并计算了不同组织和细胞系的表达谱。在每个miRNA-seq数据集中，我们发现平均有超过500个miRNA的覆盖率高于5倍，并且我们探索了每个组织和细胞系中表达最高的前五个miRNA。这个用户友好的miRmine数据库可以检索特定组织或细胞系（正常或带有疾病信息）中单个或多个miRNA的表达谱。结果可以以多种交互式、图形化和可下载的格式显示。
http://guanlab.ccmb.med.umich.edu/mirmine。
补充数据可在《生物信息学》在线获取。
