A Random Coefficients Model for Regional Co-Expression Associated with DNA Copy Number

N van Wieringen Wessel, Berkhof Johannes and A van de Wiel Mark
Additional contact information
N van Wieringen Wessel: VU University Medical Center, & VU University Amsterdam
Berkhof Johannes: VU University Medical Center
A van de Wiel Mark: VU University Medical Center & VU University Amsterdam

Statistical Applications in Genetics and Molecular Biology, 2010, vol. 9, issue 1, 30

Abstract: Regional co-expression refers to the phenomenon of contiguous genes exhibiting similar expression patterns. Among others, DNA copy number aberrations may be causally involved in regional co-expression. We propose a random coefficients model to explain regional co-expression from DNA copy number information, while modeling residual co-expression due to other causes by a correlated error structure. We show how the model parameters may be estimated (computationally efficient and consistently) from high-dimensional data, and suggest several robustifications of the estimation procedure. From the model we are able to assess whether there is a shared effect on expression levels due to the DNA copy number aberrations, but also whether this effect is homogeneous across genes. In two examples we use the proposed methodology to investigate the association between DNA copy number aberrations and regional co-expression.

Keywords: bootstrap; constrained estimation; data integration; gene expression; microarray; mRNA; quadratic programming; shrinkage (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.2202/1544-6115.1531 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sagmbi:v:9:y:2010:i:1:n:25

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/sagmb/html

DOI: 10.2202/1544-6115.1531

Access Statistics for this article

Statistical Applications in Genetics and Molecular Biology is currently edited by Michael P. H. Stumpf

More articles in Statistical Applications in Genetics and Molecular Biology from De Gruyter
Bibliographic data for series maintained by Peter Golla ().