Semblance of Heterogeneity in Collective Cell Migration

Linus J. Schumacher*, Philip K. Maini, Ruth E. Baker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Cell population heterogeneity is increasingly a focus of inquiry in biological research. For example, cell migration studies have investigated the heterogeneity of invasiveness and taxis in development, wound healing, and cancer. However, relatively little effort has been devoted to exploring when heterogeneity is mechanistically relevant and how to reliably measure it. Statistical methods from the animal movement literature offer the potential to analyze heterogeneity in collections of cell tracking data. A popular measure of heterogeneity, which we use here as an example, is the distribution of delays in directional cross-correlation. Employing a suitably generic, yet minimal, model of collective cell movement in three dimensions, we show how using such measures to quantify heterogeneity in tracking data can result in the inference of heterogeneity where there is none. Our study highlights a potential pitfall in the statistical analysis of cell population heterogeneity, and we argue that this can be mitigated by the appropriate choice of null models.

Original languageEnglish
Pages (from-to)119-+
Number of pages10
JournalCell Systems
Issue number2
Early online date26 Jul 2017
Publication statusE-pub ahead of print - 26 Jul 2017

Keywords / Materials (for Non-textual outputs)



Dive into the research topics of 'Semblance of Heterogeneity in Collective Cell Migration'. Together they form a unique fingerprint.

Cite this