Title :
Bayesian Image Modeling of cDNA Microarray Spots
Author :
Ridgway, Gerard R. ; Godsill, Simon J.
Author_Institution :
Univ. Coll. London, London
Abstract :
This letter explores the potential of Bayesian signal processing for improved modeling of microarray images and enhanced estimation of gene expression ratios. Building upon our earlier work, we describe a novel elliptical spot shape model, with a Bayesian model-fitting method. The analysis of gene replicates at the image-modeling level is also briefly discussed. Prior knowledge from neighboring spots is encompassed in the framework of a Markov random field, potentially enhancing the accuracy and reliability of ratio estimates. The techniques may be particularly beneficial for irregular, overlapping, damaged, saturated, or weakly expressed spots.
Keywords :
Bayes methods; DNA; genetics; image processing; Bayesian image modeling; Bayesian model fitting method; Bayesian signal processing; cDNA microarray spots; enhanced estimation; microarray images; of gene expression ratios; Bayesian methods; Biomedical engineering; Biomedical imaging; Biomedical signal processing; DNA; Gene expression; Image analysis; Image segmentation; Markov random fields; Shape; Bayesian; cDNA; genomics; image processing; microarray; signal processing;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2007.896378