Smoothing waves in array CGH tumor profiles.
BACKGROUND
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.


BACKGROUND
Easy-to-use R scripts, user instructions and data are available from http://www.few.vu.nl/~mavdwiel/nowaves.html.


BACKGROUND
Supplementary information are available at Bioinformatics online.
van de Wiel
Mark A
MA
Department of Epidemiology & Biostatistics, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl
Brosens
Rebecca
R
Eilers
Paul H C
PH
Kumps
Candy
C
Meijer
Gerrit A
GA
Menten
Björn
B
Sistermans
Erik
E
Speleman
Frank
F
Timmerman
Marieke E
ME
Ylstra
Bauke
B
D055028:Comparative Genomic Hybridization / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D018628:Gene Dosage; D020869:Gene Expression Profiling / Q000379:methods; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012984:Software