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PubMed · 12376092

Quality indicators increase the reliability of microarray data.

Wolfgang Raffelsberger·Doulaye Dembélé·Mike G Neubauer·Marco M Gottardis·Hinrich Gronemeyer
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Abstract

Large-scale gene expression profiling with DNA microarrays opens new dimensions to molecular biology but still lacks the overall precision of traditional low-scale techniques. We developed a novel strategy of data processing linking search stringency to quality indicators for efficient detection of low-level, regulated genes. Using retinoid-induced differentiation of NB-4 promyelocytic cells, the variation of expression profiles between biological duplicates was studied and compared with the changes induced by all-trans retinoic acid (atRA) treatment. An analysis of 4320 genes showed that retinoic acid has mainly geneactivating function in NB-4 cells. Treatment with atRA for 18 hours induced metabolic genes that may be associated with cell differentiation and signaling factors triggering later events leading to apoptosis; cytokine genes were among the highest stimulated by atRA. Notably, we identified a regulatory loop inhibiting MYC action: as MYC was downregulated, a cognate repressor of MYC was upregulated.

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Cluster AnalysisData Interpretation, StatisticalOligonucleotide Array Sequence AnalysisQuality Indicators, Health CareRegression AnalysisReverse Transcriptase Polymerase Chain ReactionJournal ArticleResearch Support, Non-U.S. Gov't

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Wolfgang Raffelsberger, Doulaye Dembélé, Mike G Neubauer, Marco M Gottardis, Hinrich Gronemeyer. 2002. Quality indicators increase the reliability of microarray data.. https://doi.org/10.1006/geno.2002.6848

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