碩士 / 國立中山大學 / 應用數學系研究所 / 106 / Bladder cancer is one of the malignant diseases in urinary system. Its common symptoms include hematuria which could be seen through eyes or urine analysis. In order to understand the effect of gene expression and mutation data on subtypes and recurrent event in patients with bladder cancer, we downloaded data from The Cancer Genome Atlas (TCGA) and applied high-dimensional analysis such as LASSO, Ridge, Adaptive Lasso and Cox model to screen gene variables, compare the performance of different models and predict the hazard of each patients. Among the selected gene candidates, we found TP53 and ERBB3 have been published in quite a few papers, which could verify our method. Not only the list of genes could help the lab to perform further analysis but also it could screen out the potential patients in advance. On the other hand, we also wrote some functions to access and deal with gene database in R language, which could be used by other researchers in the future.
| Identifer | oai:union.ndltd.org:TW/106NSYS5507009 |
| Date | January 2018 |
| Creators | Han Hsiao, 蕭涵 |
| Contributors | Chung Chang, 張中 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 47 |
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