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Correlation Statistics for cDNA Microarray Image Analysis

Radhakrishnan Nagarajan·Meenakshi Upreti
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Abstract

In this report, 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 minimizes 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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Radhakrishnan Nagarajan, Meenakshi Upreti. 2005-11-16. Correlation Statistics for cDNA Microarray Image Analysis. https://arxiv.org/abs/q-bio/0511030

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