Copy-number-aware differential analysis of quantitative DNA sequencing data
Mark D. Robinson [1,2,3,*], Dario Strbenac [3], Clare Stirzaker [3,6], Aaron L. Statham [3], Jenny Song [3], Terence P. Speed [4,5], Susan J. Clark [3,6]
[1] Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190 CH-8057 Zurich, Switzerland
[2] Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
[3] Epigenetics Laboratory, Cancer Research Program, Garvan Institute of Medical Research, Sydney 2010, New South Wales, Australia
[4] Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne 3052, Victoria, Australia
[5] Department of Medical Biology, University of Melbourne, 3050, Victoria, Australia
[6] St Vincent's Clinical School, University of NSW, Sydney, NSW, Australia
[*] Corresponding author: mark.robinson@imls.uzh.ch.
Summary
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: