Presentation Type
Poster
Faculty Mentor’s Full Name
Jeffery Good
Faculty Mentor’s Department
Division of Biological Sciences, Department of Ecology and Evolution
Abstract / Artist's Statement
As the field of computational genomics continues to expand in both potential and application, it is imperative now than ever to ensure that massive genetic sequencing datasets are properly stored in an accessible manner. This project sought to establish a practical, user-friendly, secure full-stack system for a genomics research lab (the Good Lab; thegoodlab.org) at the University of Montana. A MySQL database and connected web application was ruled the best configuration to maximize utility and accessibility for the lab’s researchers. Building the logical framework for the database, creating the server, and sourcing data occurred over several months. The data ranged from experimental details of sequencing (experiment dates, sequencing platform and provider) to metadata of the samples (specific biological specimen information, molecular protocols). A combination of lab notebooks and a master excel spreadsheet yielded over 3,500 individual sequencing experiments that spanned terabytes of archived data. These data represent over 10 years of lab sequencing efforts, with numerous examples of incomplete or non-standardized documentation. Once the database was seeded with these data, efforts transitioned to the front end. The goal was to create a web application that allowed efficient execution of basic functions (insertions, selective deletions, updates, and queries) for individuals without a MySQL background. Ultimately, the fundamental goal was accomplished: to create a clear, organized system for sequencing data with a structure and function that will permit many years of continued data collection and recall in a manner befitting the importance of the data being collected. Areas for future improvement and development for the stack were also identified.
Category
Life Sciences
Creation of a Database and Website for Genome Sequencing Data
UC South Ballroom
As the field of computational genomics continues to expand in both potential and application, it is imperative now than ever to ensure that massive genetic sequencing datasets are properly stored in an accessible manner. This project sought to establish a practical, user-friendly, secure full-stack system for a genomics research lab (the Good Lab; thegoodlab.org) at the University of Montana. A MySQL database and connected web application was ruled the best configuration to maximize utility and accessibility for the lab’s researchers. Building the logical framework for the database, creating the server, and sourcing data occurred over several months. The data ranged from experimental details of sequencing (experiment dates, sequencing platform and provider) to metadata of the samples (specific biological specimen information, molecular protocols). A combination of lab notebooks and a master excel spreadsheet yielded over 3,500 individual sequencing experiments that spanned terabytes of archived data. These data represent over 10 years of lab sequencing efforts, with numerous examples of incomplete or non-standardized documentation. Once the database was seeded with these data, efforts transitioned to the front end. The goal was to create a web application that allowed efficient execution of basic functions (insertions, selective deletions, updates, and queries) for individuals without a MySQL background. Ultimately, the fundamental goal was accomplished: to create a clear, organized system for sequencing data with a structure and function that will permit many years of continued data collection and recall in a manner befitting the importance of the data being collected. Areas for future improvement and development for the stack were also identified.