Cheng Wei-Chung, Chung I-Fang, Tsai Cheng-Fong, Huang Tse-Shun, Chen Chen-Yang, Wang Shao-Chuan, Chang Ting-Yu, Sun Hsing-Jen, Chao Jeffrey Yung-Chuan, Cheng Cheng-Chung, Wu Cheng-Wen, Wang Hsei-Wei
Research Center for Tumor Medical Science, China Medical University, Taichung 40402, Taiwan.
Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.
Nucleic Acids Res. 2015 Jan;43(Database issue):D862-7. doi: 10.1093/nar/gku1156. Epub 2014 Nov 14.
We previously presented YM500, which is an integrated database for miRNA quantification, isomiR identification, arm switching discovery and novel miRNA prediction from 468 human smRNA-seq datasets. Here in this updated YM500v2 database (http://ngs.ym.edu.tw/ym500/), we focus on the cancer miRNome to make the database more disease-orientated. New miRNA-related algorithms developed after YM500 were included in YM500v2, and, more significantly, more than 8000 cancer-related smRNA-seq datasets (including those of primary tumors, paired normal tissues, PBMC, recurrent tumors, and metastatic tumors) were incorporated into YM500v2. Novel miRNAs (miRNAs not included in the miRBase R21) were not only predicted by three independent algorithms but also cleaned by a new in silico filtration strategy and validated by wetlab data such as Cross-Linked ImmunoPrecipitation sequencing (CLIP-seq) to reduce the false-positive rate. A new function 'Meta-analysis' is additionally provided for allowing users to identify real-time differentially expressed miRNAs and arm-switching events according to customer-defined sample groups and dozens of clinical criteria tidying up by proficient clinicians. Cancer miRNAs identified hold the potential for both basic research and biotech applications.
我们之前推出了YM500,它是一个集成数据库,用于从468个人类小RNA测序数据集中进行miRNA定量、isomiR鉴定、臂转换发现和新型miRNA预测。在这个更新后的YM500v2数据库(http://ngs.ym.edu.tw/ym500/)中,我们专注于癌症miRNome,以使数据库更具疾病导向性。YM500之后开发的新的miRNA相关算法被纳入YM500v2,更重要的是,超过8000个与癌症相关的小RNA测序数据集(包括原发性肿瘤、配对的正常组织、外周血单核细胞、复发性肿瘤和转移性肿瘤的数据集)被整合到YM500v2中。新型miRNA(未包含在miRBase R21中的miRNA)不仅通过三种独立算法进行预测,还通过一种新的计算机过滤策略进行清理,并通过交联免疫沉淀测序(CLIP-seq)等湿实验室数据进行验证,以降低假阳性率。此外,还提供了一个新功能“Meta分析”,允许用户根据客户定义的样本组和由专业临床医生整理的数十个临床标准,识别实时差异表达的miRNA和臂转换事件。所鉴定的癌症miRNA在基础研究和生物技术应用方面都具有潜力。