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BMCBI
2011

Tiling array data analysis: a multiscale approach using wavelets

10 years 7 months ago
Tiling array data analysis: a multiscale approach using wavelets
Background: Tiling array data is hard to interpret due to noise. The wavelet transformation is a widely used technique in signal processing for elucidating the true signal from noisy data. Consequently, we attempted to denoise representative tiling array datasets for ChIP-chip experiments using wavelets. In doing this, we used specific wavelet basis functions, Coiflets, since their triangular shape closely resembles the expected profiles of true ChIP-chip peaks. Results: In our wavelet-transformed data, we observed that noise tends to be confined to small scales while the useful signal-of-interest spans multiple large scales. We were also able to show that wavelet coefficients due to non-specific cross-hybridization follow a log-normal distribution, and we used this fact in developing a thresholding procedure. In particular, wavelets allow one to set an unambiguous, absolute threshold, which has been hard to define in ChIP-chip experiments. One can set this threshold by requiring a si...
Alexander Karpikov, Joel S. Rozowsky, Mark Gerstei
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2011
Where BMCBI
Authors Alexander Karpikov, Joel S. Rozowsky, Mark Gerstein
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