Object Oriented Data Analysis of Cell-Well Structured Data

TL;DR

This paper proposes using cell-well unions as data objects in object oriented data analysis, demonstrating that this choice improves analysis of complex cell culture data through empirical and simulated evidence.

Contribution

It introduces a novel data object type for OODA, combining wells and cells, and shows its advantages over traditional choices in biological image analysis.

Findings

Cell-well unions outperform individual cells or wells alone in analysis.

Empirical evidence supports better data representation with cell-well unions.

Simulations confirm the benefits of the new data object choice.

Abstract

Object oriented data analysis (OODA) aims at statistically analyzing populations of complicated objects. This paper is motivated by a study of cell images in cell culture biology, which highlights a common critical issue: choice of data objects. Instead of conventionally treating either the individual cells or the wells (a container in which the cells are grown) as data objects, a new type of data object is proposed, that is the union of a well with its corresponding set of cells. This paper contains two parts. The first part is the image data analysis, which suggests empirically that the cell-well unions can be a better choice of data objects than the cells or the wells alone. The second part discusses the benefit of choosing cell-well unions as data objects using an illustrative example and simulations. This research suggests that OODA is not simply a frame work for understanding the structure of the data analysis. It leads to useful interdisciplinary discussion that gives better results through more appropriate choice of data objects, especially for complex data analyses.