Polychromatic flow cytometry is a widely used technique for gathering and analyzing cellular data. The data generated is high-dimensional, and therefore notoriously difficult to visualize by a human expert. The traditional method of plotting every pair of observables of the original high-dimensional data leads to a combinatorial explosion in the number of visualizations. The usual solution is to project the data into a lower-dimensional space while approximately preserving key properties and relationships among data points. The lower dimensional data can then be easily analyzed with the help of specialized data visualization software.
['Faraz Hussain', 'Zubir Husein', 'Neslisah Torosdagli', 'Narsingh Deo', 'Sumanta N. Pattanaik', 'Chung-Che Chang', 'Sumit Kumar Jha']
SANJAY: Automatically synthesizing visualizations of flow cytometry data using decision procedures