S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Computer Science and Engineering (컴퓨터공학부) Theses (Master's Degree_컴퓨터공학부)
BioVLAB-TCGA: 웹 기반 TCGA 오믹스 데이터 KEGG 패스웨이 매핑 시스템
- 공과대학 컴퓨터공학부
- Issue Date
- 서울대학교 대학원
- The Cancer Genome Atlas; Breast Cancer; KEGG Pathway; Omic Visualization; Gene expression analysis; RNA sequencing; Mutation; Copy number variation; TF-TG Correlation; Data mining
- 학위논문 (석사)-- 서울대학교 대학원 : 컴퓨터공학부, 2017. 2. 김선.
- TCGA, The Cancer Genome Atlas, is a database which provides omics data to public. National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI) in the United States had generated this comprehensive, multi-dimensional genomic database. Even though many scientists have tried TCGA omics data analysis, selecting target genes or patients always depends on their prior biological knowledge of their own. To enhance TCGA data usability, there needs to be a system which provides biological filtering and visualizing experimental environment. BioVLAB-TCGA system has fully implemented these requirements. In the system, graphical pathway maps from Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene selection and visualization. KEGG Pathways are fully biological meaning because they were drawn by human with biology literatures. Likewise, TCGA clinical data and PAM50 classification were applied for patients selection. Once scientists simply click the pathway and patient clinical option on web pages, then the web front-end creates URL dynamically and requests data onto
REST API. Web front-end code reads the result and visualize them as figures. KEGG pathway entries are colored after grading. while venn diagram and OncoPrint describes the landscape of selected genes and patients. With this
system, scientists can be given an insight on biological meaning of selected TCGA data.