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From the third issue of 2017, Microarrays has changed its name to High-Throughput.

Open AccessArticle

Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data

1,2,* and 1,3
Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr. 16–18, 04107 Leipzig, Germany
ecSeq Bioinformatics, Brandvorwerkstrasse 43, 04275 Leipzig, Germany
Leipzig Research Center for Civilization Diseases, Universität Leipzig, Philipp-Rosenthal-Straße 27, 04103 Leipzig, Germany
Author to whom correspondence should be addressed.
Microarrays 2014, 3(4), 322-339;
Received: 15 September 2014 / Revised: 30 September 2014 / Accepted: 8 December 2014 / Published: 16 December 2014
PDF [974 KB, uploaded 17 December 2014]


The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples. View Full-Text
Keywords: microarray; batch effects; expression analysis; quality control; RNA microarray; batch effects; expression analysis; quality control; RNA

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Fasold, M.; Binder, H. Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data. Microarrays 2014, 3, 322-339.

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