Bioinformatics Advance Access originally published online on March 10, 2009
Bioinformatics 2009 25(9):1099-1104; doi:10.1093/bioinformatics/btp132
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Smoothing waves in array CGH tumor profiles
1Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands, 2Department of Mathematics, Vrije Universiteit Amsterdam, 3Department of Pathology, VU University Medical Center, 4Department of Methodology and Statistics, Utrecht University, The Netherlands, 5Center for Medical Genetics, Ghent University Hospital, Belgium, 6Department of Clinical Genetics, VU University Medical Center and 7Heymans Institute of Psychology, DPMG, University of Groningen, The Netherlands
*To whom correspondence should be addressed.
| Abstract |
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Motivation: Many high-resolution array comparative genomic hybridization tumor profiles contain a wave bias, which makes accurate detection of breakpoints in such profiles more difficult.
Results: An efficient and highly effective algorithm that largely removes the wave bias from tumor profiles by regressing the tumor profile data on data of profiles from the clinical genetics practice. Results are illustrated on two independent datasets. The algorithm is shown to be robust against the presence of true copy number aberrations. Moreover, the smoothed profiles are able to recapitulate the aberration location and signal for simulated tumor profiles.
Availability: Easy-to-use R scripts, user instructions and data are available from http://www.few.vu.nl/~mavdwiel/nowaves.html.
Contact: mark.vdwiel{at}vumc.nl
Supplementary information: Supplementary information are available at Bioinformatics online.
Associate Editor: Martin Bishop
Received on December 23, 2008; revised on March 3, 2009; accepted on March 3, 2009