2006
DOI: 10.1038/nbt1239
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Abstract: Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titratio… Show more

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Cited by 1,849 publications
(773 citation statements)
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“…This mapping relies on the proven fundamental assumption that different microarrays are capable to reproducibly measure gene expression [25].…”
mentioning
confidence: 99%
“…This mapping relies on the proven fundamental assumption that different microarrays are capable to reproducibly measure gene expression [25].…”
mentioning
confidence: 99%
“…Microarray is widely used and accepted as a stable, well established and less costly technology to investigate gene expression data 1, 8, 14, 15. In this study based on microarray data, we established a novel method, SFC, to detect differential expression and compared it with the t test and Limma.…”
Section: Discussionmentioning
confidence: 99%
“…The MAQC project was developed by the US Food and Drug Administration (FDA) to provide standards and quality control metrics and involved six centers [Applied Biosystems (Thermo Fisher Scientific, Waltham, MA, USA), Affymetrix (Santa Clara, CA, USA), Agilent Technologies (Santa Clara, CA, USA), GE Healthcare (Chicago, IL, USA), Illumina (San Diego, CA, USA) and Eppendorf (Hamburg, Germany)] that are major providers of microarray platforms and RNA samples 1, 8. The reproducibility of the top 100 and 1000 significant genes was estimated inter‐ and intra‐platform by the three statistical methods, and heatmaps were drawn with the matrix of each batch.…”
Section: Methodsmentioning
confidence: 99%
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“…Spiked-in controls can behave perfectly and offer a way to control downstream steps but will still lead to inaccurate data when a sample is already partially degraded prior to the addition of the exogenous reference. The use of spikes for microarray data normalization has been proposed (Baker et al 2005, Shi et al 2006 and could represent one method of normalization for across-stage comparisons. Completely degraded samples raise a different concern as this condition can be assessed by microelectrophoresis and will directly affect the downstream global amplification.…”
Section: Data Processing and Analysismentioning
confidence: 99%