A Pipeline for Bio-data

Markoski, Andrew K.; Mclean, Bridget; Dang, Jonathan L.; Bernardo, Mark G.; Whittall, Fay X.; Peznola, Samantha J.

Student Work

A Pipeline for Bio-data

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Due to the lack of a pipeline that can store and analyze a wide variety of biomedical data, our team built GILBERT. GILBERT is a web application that uses Django and stores its data in PostgreSQL. It contains four main components considered essential elements of a data analysis pipeline: a system that controls which users have access to which studies, an uploader which allows users to add studies to GILBERT’s database, an interface that displays study information and metadata, and a feature that analyzes studies in the database through statistical and graphical means. To evaluate GILBERT, twenty-seven participants responded to two surveys and attended a virtual evaluation session. In the evaluation sessions, a team member read tasks to the participant while another team member scored the participant on their behavior, their ability to complete the tasks, and understanding of the system. Overall, tasks had a high completion rate. Participants rated GILBERT as easy to use and easy to understand. Differences in ratings were insignificant between different majors, amounts of experience with large amounts of data, and experience with other data handling tools such as MATLAB, Python, and SQL. These results show that GILBERT is an effective tool for biomedical data handling. Future work could make GILBERT’s uploader more flexible, allow for easier cross-study analysis, and add more options to create charts.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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