Improved Comparison of Protein Subcellular Location Patterns

A common task in cell and molecular biology is to evaluate the difference or similarity among location patterns under different circumstances. Our previous work has described an automated method to objectively compare any pair of subcellular location patterns using well-characterized numerical features. This paper describes an improved version of the previous comparison method by applying nonparametric testing and multiple testing methods. We show that the new approach has better performance for detecting differences, especially on small amounts of data. The new approach was also used to compare location patterns in a dataset containing 3D images. To demonstrate the application of the method, we collected images of drug-treated cells and then use the method to evaluate the effects of drugs on location patterns.