A sparse regulatory network of copy-number driven expression reveals putative breast cancer oncogenes
Abstract
The influence of DNA cis-regulatory elements on a gene's expression has been intensively studied. However, little is known about expressions driven by trans-acting DNA hotspots. DNA hotspots harboring copy number aberrations are recognized to be important in cancer as they influence multiple genes on a global scale. The challenge in detecting trans-effects is mainly due to the computational difficulty in detecting weak and sparse trans-acting signals amidst co-occuring passenger events. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream targets in a breast cancer dataset. Information from this network helps distinguish copy-number driven from copy-number independent expression changes on a global scale. Our result further delineates cis- and trans-effects in a breast cancer dataset, for which important oncogenes such as ESR1 and ERBB2 appear to be highly copy-number dependent. Further, our model is shown to be efficient and in terms of goodness of fit no worse than other state-of the art predictors and network reconstruction models using both simulated and real data.
Keywords
Cite
@article{arxiv.1010.1409,
title = {A sparse regulatory network of copy-number driven expression reveals putative breast cancer oncogenes},
author = {Yinyin Yuan and Christina Curtis and Carlos Caldas and Florian Markowetz},
journal= {arXiv preprint arXiv:1010.1409},
year = {2016}
}
Comments
Accepted at IEEE International Conference on Bioinformatics & Biomedicine (BIBM 2010)