Microarrays denoising via smoothing of coefficients in wavelet domain
We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on a smoothing of the coefficients of the highest subbands. Specifically, we decompose the noisy microarray into wavelet subbands, apply smoothing within each highest subband,...
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | We describe a novel method for removing noise (in wavelet domain) of unknown
variance from microarrays. The method is based on a smoothing of the
coefficients of the highest subbands. Specifically, we decompose the noisy
microarray into wavelet subbands, apply smoothing within each highest subband,
and reconstruct a microarray from the modified wavelet coefficients. This
process is applied a single time, and exclusively to the first level of
decomposition, i.e., in most of the cases, it is not necessary a
multirresoltuion analysis. Denoising results compare favorably to the most of
methods in use at the moment. |
---|---|
DOI: | 10.48550/arxiv.1807.11571 |