MODELING ASSOCIATION BETWEEN DNA COPY NUMBER AND GENE EXPRESSION WITH CONSTRAINED PIECEWISE LINEAR REGRESSION SPLINES

DNA copy number and mRNA expression are widely used data types in cancer studies, which combined provide more insight than separately. Whereas in existing literature the form of the relationship between these two types of markers is fixed a priori, in this paper we model their association. We employ...

Full description

Saved in:
Bibliographic Details
Published in:The annals of applied statistics 2013-06, Vol.7 (2), p.823-845
Main Authors: Leday, Gwenaël G. R., van der Vaart, Aad W., van Wieringen, Wessel N., van de Wiel, Mark A.
Format: Article
Language:English
Subjects:
Breast cancer
confidence bands
constrained inference
Datasets
DNA
DNA copy number
Gene expression
Genes
Linear models
Linear regression
Matrices
Messenger RNA
model selection
mRNA expression
Parametric models
regression splines
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:DNA copy number and mRNA expression are widely used data types in cancer studies, which combined provide more insight than separately. Whereas in existing literature the form of the relationship between these two types of markers is fixed a priori, in this paper we model their association. We employ piecewise linear regression splines (PLRS), which combine good interpretation with sufficient flexibility to identify any plausible type of relationship. The specification of the model leads to estimation and model selection in a constrained, nonstandard setting. We provide methodology for testing the effect of DNA on mRNA and choosing the appropriate model. Furthermore, we present a novel approach to obtain reliable confidence bands for constrained PLRS, which incorporates model uncertainty. The procedures are applied to colorectal and breast cancer data. Common assumptions are found to be potentially misleading for biologically relevant genes. More flexible models may bring more insight in the interaction between the two markers.
ISSN:1932-6157
1941-7330
DOI:10.1214/12-AOAS605