Bioinformatics Advance Access published online on March 10, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp132
Smoothing waves in array CGH tumor profiles
aDepartment of Epidemiology & Biostatistics, cDepartment of Pathology, fDepartment of Clinical Genetics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam; bDepartment of Mathematics, Vrije Universiteit Amsterdam; dDepartment of Methodology and Statistics, Utrecht University; eHeymans Institute of Psychology, DPMG, University of Groningen, The Netherlands; gCenter for Medical Genetics, Ghent University Hospital, Belgium.
*To whom correspondence should be addressed. Dr. Mark van de Wiel, E-mail: mark.vdwiel{at}vumc.nl
| Abstract |
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Motivation: Many high-resolution array CGH 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 data sets. 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 is available at Bioinformatics online.
Associate Editor: Prof. Martin Bishop
Received on December 23, 2008; revised on March 3, 2009; accepted on March 3, 2009