Correlation Statistics for cDNA Microarray Image Analysis

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dc.creatorNagarajan, Radhakrishnan
dc.creatorUpreti, Meenakshi
dc.date2005-11-16
dc.date.accessioned2026-07-07T06:52:35Z
dc.date.available2026-07-07T06:52:35Z
dc.descriptionIn 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.
dc.description25 Pages, 8 Figures
dc.identifierhttps://arxiv.org/abs/q-bio/0511030
dc.identifierhttp://arxiv.org/abs/q-bio/0511030
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/105346
dc.subjectGenomics
dc.subjectQuantitative Methods
dc.titleCorrelation Statistics for cDNA Microarray Image Analysis
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