Copy-number-aware differential analysis of quantitative DNA sequencing data
Mark D. Robinson [1,2,3,*], Dario Strbenac , Clare Stirzaker [3,6], Aaron L. Statham , Jenny Song , Terence P. Speed [4,5], Susan J. Clark [3,6]
 Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190 CH-8057 Zurich, Switzerland
 Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
 Epigenetics Laboratory, Cancer Research Program, Garvan Institute of Medical Research, Sydney 2010, New South Wales, Australia
 Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne 3052, Victoria, Australia
 Department of Medical Biology, University of Melbourne, 3050, Victoria, Australia
 St Vincent's Clinical School, University of NSW, Sydney, NSW, Australia
[*] Corresponding author: email@example.com.
Developments in microarray and high throughput sequencing (HTS) technologies have resulted in a rapid expansion of research into epigenomic changes that occur in normal development and in the progression of disease, such as cancer. Not surprisingly, copy number variation (CNV) has a direct effect on HTS read densities and can therefore bias differential detection results. We have developed a flexible approach called ABCD-DNA (Affinity Based Copy-number-aware Differential quantitative DNA sequencing analyses) that integrates CNV and other systematic factors directly into the differential enrichment engine.
Supplementary Data (semi-processed), R Code for all Figures and analyses: