Dr. Mario Roederer
Revolutionizing Flow Cytometry
Roederer also took advantage of syntax coloring to identify keywords and constructs. “It’s a huge timesaver, because you see immediately when you’ve made a typo or when something doesn’t make sense.
“And the IDE keeps everything organized for you; that’s a huge increase in efficiency.”
Small Details, Big Impact
“It seems likes a small thing, but features like syntax coloring make an enormous difference in your ability to program and to develop applications, and we’ve implemented similar types of features in FlowJo.
“For instance, we alert users with color cues when there are potential problems with their data so they get subconscious feedback. This subtle feedback allows users to focus on the important task, to be distracted only when there is a critical issue.
“It’s like riding a bicycle. When you have to make a turn, you don’t actually think ‘I have to make a turn now’ — your body just does it. If you ride over a bump, you may not have seen the bump. But you get the subconscious feedback that you have to do something differently.
“Those subtle things are important to making an efficient user interface, both from the analysis and the programming paradigm. They’re often the features that users never even recognize.”
Smooth Revisions
When Roederer and Treister released FlowJo in 1997, it provided powerful new tools for subset and statistics analysis. Since then, the software has been expanded to provide specialized analysis platforms for certain branches of science as well as “some very nice new automated tools.
“In seven years, we’ve undergone three major revisions,” Roederer says, “with minor revisions every two to three months.
“Adding an entirely new analysis platform is remarkably fast, because we already have the internal templates. We take existing tools and just revise the user interface and the algorithm. Everything else is the same.”
New Research Platforms
When FlowJo added a Kinetics platform, it gave researchers the ability to analyze data as a function of time. Another platform, the Proliferation platform, “is a very useful tool for determining how many times a cell has divided after you stimulated it,” Roederer says. This is a crucial question for researchers who want to know how different stimuli or drugs affect cells.
“We alert users with color cues when there are potential problems with their data. This subtle feedback allows them to focus on the important task, to be distracted only when there is a critical issue.”
“Users stain cells with a fluorescent dye and every time the cells divide, half of the dye moves into each of the daughter cells. Over a period of days, you get successive snapshots — some of the cells have divided four times, some two times, some not at all.
“So we built a specialized platform that supports this kind of analysis. The program analyzes the distribution and gates out or identifies the cells that have divided none, one, two, three and so forth.”
Other platforms allow researchers to model DNA content of dividing cells, use sophisticated cluster tools to identify subsets in n-dimensional space, compare multidimensional distributions of data, calibrate fluorescence parameters and compensate multi-spectral data.
New Tools
FlowJo also incorporates new ways of working.
“For example, users looking at a scatter plot of the data want to draw a polygon or an ellipse around cells of interest in order to drill down to further analyze only those cells. We implemented a tool where the program actually creates regions of interest for users as they mouse over the plot.
