GWAS Data

Inspiration

Data visualization through R studio showing the underrepresentation of specific areas when it comes to genome analysis.

What it does

The interactive map will allow one to see the concentration of depression cases and who was tested. This will also allow one to see the lack of diversity found in the collected samples. The colorful gradient shows the high areas of testing compared to the low. That effect makes it easier for the general population to understand concepts that we bioinformaticists are familiar with.

How we built it

We built a tool that accepts data about Genome-wide association studies. Used data to create visualizations of where the data originates from and to provide relative quantity. We used R for data analysis, and we used Quorto to build a data report containing our analysis.

Challenges we ran into

Separating our data so we can make a bar graph showing the three variables, Total cases, Depression Cases, and Control Cases. Trying to learn how to at least decently code to not drag the team down. Pushing past the point of tiredness to accomplish set goals.

Accomplishments that we're proud of

Practically everything. The interactive map, color gradient, bar plots, and data visualization overall feel pretty amazing and friendly.

What we learned

That some things should be taken in smaller bites so you don’t become overwhelmed with the bigger picture. Familiarizing ourselves with the R studio program. Figuring out how to work with people who are different than you in multiple areas. How to prioritize what is important over something that isn’t as important

What's next for the map

We will update the interface to JavaScript to allow synchronous changes and intractability. We will also update the backend to have clear data formatting requirements and build saving and storage for a clean all-encompassed workflow.