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*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 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
Article numbere22323
StatePublished - 13 Mar 2017
Externally publishedYes


FundersFunder number
National Institutes of HealthP01 GM096971, GM713165, P01 GM103723
National Institute of General Medical SciencesR01GM073165
Cancer Prevention and Research Institute of TexasR1225


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