Authors: Martin Becker, Dorien Feyaerts, Ina A. Stelzer, Eloise Berson Alan L. Chang, Geetha Saarunya, Clarke, Anthony Culos, Davide De Francesco, Camilo Espinosa, Yeasul Kim, Ivana Maric Samson Mataraso, Seyedeh Neelufar Payrovnaziri, Thanaphong Phongpreecha, Neal G. Ravindra, Natalie Stanley, Sayane Shome, Yuqi Tan Melan Thuraiappah, Lei Xue, Gary Shaw, David Stevenson, Martin S. Angst, Brice Gaudilliere Nima Aghaeepour
Summary: Biological systems comprise a vast amount of intricate processes that are deeply intertwined and carefully coordinated in order to enable complex functions. Internal and external challenges can introduce major disruptions to such systems requiring dynamic functional adaptions on how the corresponding processes interact. However, complex disruption patterns are hard to capture and analyze, particularly when focusing on biomarkers individually without accounting for their dependencies. To address this, we provide CoDi , an easy to use and highly flexible open-source package that allows to quantify disruption characteristics of biomarker networks across conditions and timepoints, and discover modules with exceptional disruption profiles. CoDi employs the notion of correlation disruption which quantifies functional disruptions and enables a novel perspective on the coordination and adaption of biological systems to internal and external challenges. Our examples illustrate the scope of CoDi , by revealing coordinated functional adaptions of the immune system during pregnancy.
Data and code availability:
- Source code for reproduction of the results is available here.
- The healthy pregnancy data used in our manuscript previously analyzed in Aghaeepour et al. 2017 and Ghaemi et al. 2019 and is available here.
- The preeclampsia data used in our manuscript previously analyzed in Han et al. 2029 is available here.