Liudas Panavas , Michael Davinroy, Ritwik Anand
Service-Learning Course Project as part of CS 7250 S21 Information Visualization: Theory and Applications, taught by Prof. Cody Dunne, Data Visualization @ Khoury, Northeastern University.
Our partners, Data Tecnica, NIH, and the Center Center for Alzheimer’s and Related Dementias, want to allow domain experts in Genomics to leverage the increasing amounts of data generated through experiments about the relationship between sets of genes to a Neurodegenerative Disorder. We utilize visualization techniques so that specialized experts who only know a subset of the data can easily explore the full dataset to generate new hypothesis for future research. Our visualization can be found here.
Hi, everyone! For our project, we are creating a tool to visualize metadata of research correlating specific genes to neurodegenerative diseases given specific biological tests. The use of this tool is for biologists, who may specialize in studying very specific subsets of genes and/or diseases, to create new hypotheses. To use omicSynth, click on a set (usually one or two, since it's still a bit slow) of checkboxes to the left. These represent correlation values between genes and tests. This will open up a series of bar graphs. The top one is a stacked bar graph combining the values of the the remaining bar graphs that show values for a specific test that has been checked. Any of these bar graphs can be sorted by ascending or descending values by clicking the cooresponding button near each bar chart (this will also change the other graphs to meet this order, so that they all line up). Additionally, we have scented widgets that are a swarm graphs that function as filters for the data. Move the gray shaded box to select a range of genes to be shown by linking to the bar graphs. When they are shown in the bar graphs, the genes will be highlighted in red. If they are not selected (either if they are outside the box, not shown due to space, or do not fall into the range of every selected filter, etc.), they will appear as a opaque black dot. Finally, we have a parallel coordinates and table view for more specific genes. Currently, these are not linked and are static, but the final visualization will have them be interactive and linked with gene selection. Enjoy!