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Correlation Statistics for cDNA Microarray Image Analysis

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2 Author(s)
Nagarajan, R. ; Center for Aging, Arkansas Univ. for Med. Sci., Little Rock, AR ; Upreti, M.

In this paper, correlation of the pixels comprising a microarray spot is investigated. Subsequently, correlation statistics, namely, Pearson correlation and Spearman rank correlation, are used to segment the foreground and background intensity of microarray spots. The performance of correlation-based segmentation is compared to clustering-based (PAM, k-means) and seeded-region growing techniques (SPOT). It is shown that correlation-based segmentation is useful in flagging poorly hybridized spots, thus minimizing false-positives. The present study also raises the intriguing question of whether a change in correlation can be an indicator of differential gene expression

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Computational Biology and Bioinformatics, IEEE/ACM Transactions on  (Volume:3 ,  Issue: 3 )