SANJAY: Automatically synthesizing visualizations of flow cytometry data using decision procedures

摘要

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.