A novel stationary wavelet denoising algorithm for array-based DNA Copy Number data
International Journal of Bioinformatics Research and Applications
Automatic Bayesian quantile regression curve fitting
Statistics and Computing
GIMscan: a new statistical method for analyzing whole-genome array CGH data
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Approximation algorithms for speeding up dynamic programming and denoising aCGH data
Journal of Experimental Algorithmics (JEA)
Detection of chromosomal abnormalities using high resolution arrays in clinical cancer research
Journal of Biomedical Informatics
CNV detection method optimized for high-resolution arrayCGH by normality test
Computers in Biology and Medicine
Novel multi-sample scheme for inferring phylogenetic markers from whole genome tumor profiles
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
Computational Statistics & Data Analysis
Novel Multisample Scheme for Inferring Phylogenetic Markers from Whole Genome Tumor Profiles
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Motivation: Plots of array Comparative Genomic Hybridization (CGH) data often show special patterns: stretches of constant level (copy number) with sharp jumps between them. There can also be much noise. Classic smoothing algorithms do not work well, because they introduce too much rounding. To remedy this, we introduce a fast and effective smoothing algorithm based on penalized quantile regression. It can compute arbitrary quantile curves, but we concentrate on the median to show the trend and the lower and upper quartile curves showing the spread of the data. Two-fold cross-validation is used for optimizing the weight of the penalties. Results: Simulated data and a published dataset are used to show the capabilities of the method to detect the segments of changed copy numbers in array CGH data. Availability: Software for R and Matlab is available. Contact: p.eilers@lumc.nl