SUMMARY: DNA copy number and mRNA expression are commonly used data types in 
cancer studies. Available software for integrative analysis arbitrarily fixes 
the parametric form of the association between the two molecular levels and 
hence offers no opportunities for modelling it. We present a new tool for 
flexible modelling of this association. PLRS uses a wide class of interpretable 
models including popular ones and incorporates prior biological knowledge. It is 
capable to identify the gene-specific type of relationship between gene copy 
number and mRNA expression. Moreover, it tests the strength of the association 
and provides confidence intervals. We illustrate PLRS using glioblastoma data 
from The Cancer Genome Atlas.
AVAILABILITY AND IMPLEMENTATION: PLRS is implemented as an R package and 
available from Bioconductor (as of version 2.12; http://bioconductor.org). 
Additional code for parallel computations is available as Supplementary 
Material.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics 
online.