期刊
RNA BIOLOGY
卷 17, 期 11, 页码 1666-1673出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/15476286.2019.1679585
关键词
Cancer survival analysis; non-coding RNA; lincRNA; pseudogene
资金
- Comprehensive Cancer Centre at the University of New Mexico
- Bioinformatics Shared Resources and the Biostatistics Shared Resources at The Comprehensive Cancer Centre
- Shanghai Science and Technology Commission [16411966000]
- interdisciplinary Programme of Shanghai Jiaotong University [YG2014QN22]
- Science and Technology Commission Shanghai Municipality [STC5M15DZ2270400]
- Natural Science Foundation of China [81572245, 81402571]
- Collaborative Research Project of Transformational Medicine Collaborative Innovation Centre [TM201822]
- [P30CA118100]
Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA?s biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据