Heteromotility is a tool for analyzing cell motility in a quantitative manner. Heteromotility takes timelapse imaging data as input and calculates various ‘motility features’ that can be used to generate a ‘motility fingerprint’ for a given cell. The tool contains basic image segmentation and cell tracking components, but can also be used to analyze cell trajectories derived from another software tool. By analyzing more features of cell motility than most common cell tracking methods, Heteromotility may be able to identify novel heterogenous motility phenotypes.

Heteromotility also contains a suite of tools to quantify and visualize cell state spaces, and dynamic state transitions within the state space. While these tools were developed for use with Heteromotility features, they may be applied to any arbitrary time-series feature set.

We’ve posted a pre-print applying Heteromotility analysis to quantify dynamic cell state transitions in muscle stem cells and a cancer cell model. Check it out on bioRxiv!


Kimmel JC, Chang AY, Brack AS, Marshall WF (2018) Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance. PLOS Computational Biology 14(1): e1005927. https://doi.org/10.1371/journal.pcbi.1005927


Source Code


Motility Video Gallery

Videos below are presented with colored numeric labels indicating the "motility state," each cell occupies, as described in the text of our recent pre-print. Colored circles mark the locations visited by the cells with a corresponding colored label.

All videos are presented at 10 frames per second, where frames are 6.5 minutes apart in real-time.

Muscle Stem Cells (MuSCs)


Mouse Embryonic Fibroblasts - MycRas Transformed


Mouse Embryonic Fibroblasts - Wild-type