Department of Preventive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, PR China.
Department of Pathology, Stanford University School of Medicine, Palo Alto, CA 94305, USA.
Future Oncol. 2019 Sep;15(27):3103-3110. doi: 10.2217/fon-2019-0296. Epub 2019 Aug 1.
To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan-Meier survival plot with hazard ratio and log-rank p-value. OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp.
开发一个免费且快速的在线分析工具，使用户能够轻松地研究肾透明细胞癌（KIRC）中感兴趣基因的预后潜力。从公共基因表达综合数据库和癌症基因组图谱数据库中收集了总共 629 个 KIRC 病例的基因表达谱数据和临床随访信息。构建了一个名为在线 KIRC 共识生存分析（OSkirc）的 Web 应用程序，可用于探索 KIRC 中感兴趣基因的预后意义。通过 OSkirc，用户只需输入基因符号，即可获得带有风险比和对数秩 p 值的 Kaplan-Meier 生存图。OSkirc 对于基础和转化研究人员筛选和验证 KIRC 基因的预后潜力非常有价值，可在 http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp 上公开访问。
