PT  - JOURNAL ARTICLE
AU  - Assaf Zaritsky
AU  - Uri Obolski
AU  - Zhuo Gan
AU  - Carlos R. Reis
AU  - Zuzana Kadlecova
AU  - Yi Du
AU  - Sandra L. Schmid
AU  - Gaudenz Danuser
TI  - Decoupling global biases and local interactions between cell biological variables
AID  - 10.1101/038059
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 038059
4099  - http://biorxiv.org/content/early/2017/02/14/038059.short
4100  - http://biorxiv.org/content/early/2017/02/14/038059.full
AB  - 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. The DeBias software package is freely accessible online via a web-server at https://debias.biohpc.swmed.edu.Impact statement: DeBias, a generic method to decompose and quantify the confounding, global factors and direct interactions of pairwise interacting variables.