Decoupling global biases and local interactions between cell biological variables

Assaf Zaritsky, Uri Obolski, Zhuo Gan, Carlos R. Reis, Zuzana Kadlecova, Yi Du, Sandra L. Schmid, Gaudenz Danuser

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Analysis of coupled variables is a core concept of cell biological inference, with co-localization of two molecules as a proxy for protein interaction being a ubiquitous example. However, external effectors may influence the observed co-localization independently from the local interaction of two proteins. Such global bias, although biologically meaningful, is often neglected when interpreting co-localization. Here, we describe DeBias, a computational method to quantify and decouple global bias from local interactions between variables by modeling the observed co-localization as the cumulative contribution of a global and a local component. We showcase four applications of DeBias in different areas of cell biology, and demonstrate that the global bias encapsulates fundamental mechanistic insight into cellular behavior.

Original languageEnglish (US)
Article numbere22323
StatePublished - Mar 13 2017

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)


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