Decoupling global biases and local interactions between cell biological variables
- UT Southwestern Medical Center, United States
- University of Oxford, United Kingdom
Abstract
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.
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Author details
Funding
Cancer Prevention and Research Institute of Texas (R1225)
- Gaudenz Danuser
National Institutes of Health (P01 GM103723)
- Gaudenz Danuser
National Institutes of Health (PO1 GM713165)
- Sandra L Schmid
- Gaudenz Danuser
EMBO (postdoctoral fellowship)
- Uri Obolski
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2017, Zaritsky et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Decoupling global biases and local interactions between cell biological variables
eLife 6:e22323.
https://doi.org/10.7554/eLife.22323
