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https://scholarbank.nus.edu.sg/handle/10635/177441
DC Field | Value | |
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dc.title | A PAN-CANCER ANALYSIS OF ALTERNATIVE PROMOTERS USING RNA-SEQ DATA | |
dc.contributor.author | DENIZ DEMIRCIOGLU | |
dc.date.accessioned | 2020-10-14T18:00:25Z | |
dc.date.available | 2020-10-14T18:00:25Z | |
dc.date.issued | 2019-08-21 | |
dc.identifier.citation | DENIZ DEMIRCIOGLU (2019-08-21). A PAN-CANCER ANALYSIS OF ALTERNATIVE PROMOTERS USING RNA-SEQ DATA. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/177441 | |
dc.description.abstract | Most human protein-coding genes transcribe multiple isoforms via alternative splicing and are regulated by multiple, distinct promoters. The wide availability of RNA-seq data allows the examination of alternative splicing, yet study of alternative promoters mostly relies on experimental approaches such ChIP-Seq and CAGE with limited availability. Therefore, the large-scale comprehensive analysis of promoter landscape is still not feasible experimentally and computationally. Here, we developed a computational method called proActiv to infer promoter activity by using widely available RNA-Seq data. Furthermore, by utilizing our promoter activity estimates, we developed a statistical framework to identify alternative promoters displaying context-dependent regulation. We find that promoters are deregulated across tissues, cancer types, and patients; and showed that promoter activity estimates could help us interpret noncoding promoter mutations. Our study suggests that promoter activity can be robustly and efficiently estimated using RNA-Seq data and thew dynamic landscape of promoters shapes the tissue and cancer transcriptome. | |
dc.language.iso | en | |
dc.subject | transcriptomics, RNA-sequencing, bioinformatics, transcriptional regulation, cancer | |
dc.type | Thesis | |
dc.contributor.department | COMPUTER SCIENCE | |
dc.contributor.supervisor | Wing Kin Sung | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (SOC) | |
dc.identifier.orcid | 0000-0001-7857-0407 | |
Appears in Collections: | Ph.D Theses (Open) |
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DemirciogluD.pdf | 7.3 MB | Adobe PDF | OPEN | None | View/Download |
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