Tiling array data analysis: a multiscale approach using wavelets.

ABSTRACT:

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 de

SUBMITTER: Karpikov A 

PROVIDER: S-EPMC3055839 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature