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BMC Biology

, 1:1

First Online: 28 November 2003Received: 18 August 2003Accepted: 28 November 2003

Abstract

BackgroundThe assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed.

ResultsWe used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates.

ConclusionThe strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http:-www.sadovsky.wustl.edu-tscore.html.

Electronic supplementary materialThe online version of this article doi:10.1186-1741-7007-1-1 contains supplementary material, which is available to authorized users.

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Autor: Vikram Budhraja - Edward Spitznagel - W Timothy Schaiff - Yoel Sadovsky

Fuente: https://link.springer.com/article/10.1186/1741-7007-1-1



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