Application Note: Advanced Label-Free Classification of Cell Morphology Subpopulations

A cell’s morphology contains a wealth of information that can be used to make decisions around cell culture conditions and responses during assay development. Traditional methods for describing this information are subjective, potentially resulting in loss of data and a lack of robustness and reproducibility within cell-based assays.

Objective quantification of morphology, on the other hand, enables researchers to make data-driven decisions for successful cell culture propagation and experimentation. Here, morphological data can be used as a kinetic readout to determine compound effects - for example, counting the number of cells with viable versus apoptotic morphology gives a direct measure of cytotoxicity. Utilizing label-free image analysis to perform these measurements has the added benefit of being completely nonperturbing to cells, ensuring the data is free of method-related artifacts. This is especially vital when using highly sensitive or rare cell types.

The Incucyte® Advanced Label-Free Classification Analysis Software Module - an add-on to the Incucyte® Cell-by-Cell Analysis Software Module - enables users to identify two classes of cells by their morphology and quantified over time in kinetic assays. Automated quantification of cell morphology through multivariate analysis is used to identify multiple morphological features such as cell area, texture, brightness and symmetry. These parameters then create an unbiased, meaningful score used to classify cells into two user-identified groups.


In this application note, we will demonstrate the use of the Incucyte® Advanced Label-Free Classification Analysis Software Module within three biological models:

  • Label-free live | dead assay
  • Detection of mitotic cells within a cell cycle assay
  • Label-free differentiation and morphological analysis of macrophage subpopulations


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