Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/177441
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dc.titleA PAN-CANCER ANALYSIS OF ALTERNATIVE PROMOTERS USING RNA-SEQ DATA
dc.contributor.authorDENIZ DEMIRCIOGLU
dc.date.accessioned2020-10-14T18:00:25Z
dc.date.available2020-10-14T18:00:25Z
dc.date.issued2019-08-21
dc.identifier.citationDENIZ DEMIRCIOGLU (2019-08-21). A PAN-CANCER ANALYSIS OF ALTERNATIVE PROMOTERS USING RNA-SEQ DATA. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/177441
dc.description.abstractMost 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.isoen
dc.subjecttranscriptomics, RNA-sequencing, bioinformatics, transcriptional regulation, cancer
dc.typeThesis
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.supervisorWing Kin Sung
dc.description.degreePh.D
dc.description.degreeconferredDOCTOR OF PHILOSOPHY (SOC)
dc.identifier.orcid0000-0001-7857-0407
Appears in Collections:Ph.D Theses (Open)

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