Building a database of cancer genomics data

• Main Author: Chern, Shan Ni
• Other Authors: Zheng Jie
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems
• Online Access: http://hdl.handle.net/10356/62848
• Institution: Nanyang Technological University

Cancer is known to be a genetic disease. Due to the inherent complexity of cancer, large-scale genomics datasets are therefore required to study the diseases. The purpose of this project, is to download publically available data about cancer (including DNA sequences, gene expression, and clinical trial data) from TCGA (The Cancer Genome Atlas), RNASeqV2 is used to determine the gene expression level, and integrate them into a NoSQL database. The motivation for this project was to provide a centralized database to speed up and increase the accuracy of cancer research or data analysis with the ability to use large-scale genomics datasets. Programming interfaces was developed to ease the access and maintenance of the database. Along with the interfaces, different functions were developed for the database administrator and system user. Database administrator can perform insertion, edition, and deletion of datasets to the database. Insertion of datasets will allow the administrator to select a desired file to upload. Edition and deletion of the data will allow the administrator to select or search a particular record that was in the database. System user can perform query such as search for a particular gene’s information and average scaled estimate for a particular gene. The development tasks of this project follow closely to the iterative Software Development Lifecycle (SDLC) which will be presented in this report. With reference to the developed database, further development and enhancement can be made in order to better facilitate the application users. The future development work can include allowing the database to draw out the relationship between the genes found in different cancer with the building of a larger database.