Flexible analysis of digital PCR experiments using generalized linear mixed models

Authors

Matthijs Vynck, Ghent University, Belgium
J Vandesompele, Biogazelle, Ghent University
Nele Nijs, Biogazelle
Björn Menten, Ghent University
Ariane De Ganck, Biogazelle
Olivier Thas, University of WollongongFollow

RIS ID

108305

Publication Details

Vynck, M., Vandesompele, J., Nijs, N., Menten, B., De Ganck, A. & Thas, O. (2016). Flexible analysis of digital PCR experiments using generalized linear mixed models. Biomolecular Detection and Quantification, 9 1-13.

Abstract

The use of digital PCR for quantification of nucleic acids is rapidly growing. A major drawback remains the lack of flexible data analysis tools. Published analysis approaches are either tailored to specific problem settings or fail to take into account sources of variability. We propose the generalized linear mixed models framework as a flexible tool for analyzing a wide range of experiments. We also introduce a method for estimating reference gene stability to improve accuracy and precision of copy number and relative expression estimates. We demonstrate the usefulness of the methodology on a complex experimental setup.