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 journalArticle

5 Citations (Scopus)

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.

Original languageEnglish (US)
Article numbere22323
JournaleLife
Volume6
DOIs
StatePublished - Mar 13 2017

Fingerprint

Cell Communication
Cytology
Proxy
Computational methods
Cell Biology
Proteins
Molecules

ASJC Scopus subject areas

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

Cite this

Zaritsky, A., Obolski, U., Gan, Z., Reis, C. R., Kadlecova, Z., Du, Y., ... Danuser, G. (2017). Decoupling global biases and local interactions between cell biological variables. eLife, 6, [e22323]. https://doi.org/10.7554/eLife.22323

Decoupling global biases and local interactions between cell biological variables. / Zaritsky, Assaf; Obolski, Uri; Gan, Zhuo; Reis, Carlos R.; Kadlecova, Zuzana; Du, Yi; Schmid, Sandra L.; Danuser, Gaudenz.

In: eLife, Vol. 6, e22323, 13.03.2017.

Research output: Contribution to journalArticle

Zaritsky A, Obolski U, Gan Z, Reis CR, Kadlecova Z, Du Y et al. Decoupling global biases and local interactions between cell biological variables. eLife. 2017 Mar 13;6. e22323. https://doi.org/10.7554/eLife.22323
Zaritsky, Assaf ; Obolski, Uri ; Gan, Zhuo ; Reis, Carlos R. ; Kadlecova, Zuzana ; Du, Yi ; Schmid, Sandra L. ; Danuser, Gaudenz. / Decoupling global biases and local interactions between cell biological variables. In: eLife. 2017 ; Vol. 6.
@article{954e63df48884e35babcb401144ff6c8,
title = "Decoupling global biases and local interactions between cell biological variables",
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.",
author = "Assaf Zaritsky and Uri Obolski and Zhuo Gan and Reis, {Carlos R.} and Zuzana Kadlecova and Yi Du and Schmid, {Sandra L.} and Gaudenz Danuser",
year = "2017",
month = "3",
day = "13",
doi = "10.7554/eLife.22323",
language = "English (US)",
volume = "6",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",

}

TY - JOUR

T1 - Decoupling global biases and local interactions between cell biological variables

AU - Zaritsky, Assaf

AU - Obolski, Uri

AU - Gan, Zhuo

AU - Reis, Carlos R.

AU - Kadlecova, Zuzana

AU - Du, Yi

AU - Schmid, Sandra L.

AU - Danuser, Gaudenz

PY - 2017/3/13

Y1 - 2017/3/13

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=85018883351&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018883351&partnerID=8YFLogxK

U2 - 10.7554/eLife.22323

DO - 10.7554/eLife.22323

M3 - Article

C2 - 28287393

AN - SCOPUS:85018883351

VL - 6

JO - eLife

JF - eLife

SN - 2050-084X

M1 - e22323

ER -