Feature extraction and signal processing for nylon DNA microarrays.

Détails

Ressource 1Télécharger: BIB_30851.P001.pdf (2498.40 [Ko])
Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_30851
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Feature extraction and signal processing for nylon DNA microarrays.
Périodique
BMC Genomics
Auteur⸱e⸱s
Lopez F., Rougemont J., Loriod B., Bourgeois A., Loï L., Bertucci F., Hingamp P., Houlgatte R., Granjeaud S.
ISSN
1471-2164
Statut éditorial
Publié
Date de publication
2004
Volume
5
Numéro
1
Pages
38
Langue
anglais
Notes
Publication types: Comparative Study ; Evaluation Studies ; Journal Article ; Research Support, Non-U.S. Gov't
Résumé
BACKGROUND: High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. RESULTS: We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis). CONCLUSIONS: Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper.
Mots-clé
Algorithms, Animals, Arabidopsis Proteins, Bias (Epidemiology), Breast Neoplasms, Carbon-Oxygen Ligases, Cluster Analysis, DNA, Neoplasm, DNA, Plant, Densitometry, Discriminant Analysis, Gene Expression Profiling, Humans, Image Processing, Computer-Assisted, Mice, Nylons, Oligonucleotide Array Sequence Analysis, Phosphorus Radioisotopes, Polymerase Chain Reaction, RNA, Messenger, Reproducibility of Results, Signal Processing, Computer-Assisted, Software
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/11/2007 9:59
Dernière modification de la notice
20/08/2019 13:15
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