Inspiration

FlowJo provides a very easy to use interface for veteran wet-lab scientists. For new faces to the art form that is flow cytometry, it may take some time to become acquainted with data analysis. Instead of clicking around to find the data we want to interpret, we thought it would be easier to gather the most necessary data for analysis all in one place via a web plugin.

Wet lab instruments are very expensive, and many academic institutions cannot afford more than one if any at all. Based on an experience with having a class line up single-file to watch the lab instructor demonstrate a run on a flow cytometer it became apparent that there must be an easier, faster way to both visualize the data and interpret it. Another use would include sharing real, interactive data with students in online classrooms, instead of using screenshots and expecting them to understand the data.

What it does

Flow cytometry output from the instrument are submitted to a server where it combines all figures needed to interpret and classify the cells present within the sample. This plugin provides an interface through a front-end application via web-socket.

How I built it

We built with Java and NetbeansID connected to the FlowJo API.

Challenges I ran into

Coming from a group comprised of three novice coders, two of which were biologists and the other 'a new-to-the-game' computer engineer/application developer and strong full-stack web developer, the biggest challenge was articulating the biological interpretation of the data.

Accomplishments that I'm proud of

Gaining the communication skills that allowed for translation from idea to application.

What I learned

I learned about what it takes to integrate a dynamic dataset that will always be different from the last into an equally dynamic visualization tool on the web that would allow for others to view the data easily while simultaneously telling the story of what was going on at the cellular level.

What's next for FLOWJO.io - FLOWJO challenge

The next step would be to include datasets from link and incorporating similar organisms and applications into the plugin. Another feature would be adding the important functionality of being able to track a certain cell or sample's viability over time in a one page integrated UI as scientists must check in on their given organism on a daily basis.

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