Separating Outliers from HCS


Please see here for a description of the data set used in this tutorial.


HCS data contain a lot of outliers, often resulting from primitive image processing algorithms. Because most of the variables in an HCS data set are directly or indirectly based on nuclei identified by image analysis, it is a good idea to first look at DNA profiles to identify and remove outliers; otherwise, the garbage that goes in comes out to clutter otherwise good analysis.

Identifying Outlier Cells

Getting the "Good" Cells