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

Microarrays

Mario Fasold¹  Hans Binder¹ 

[1] Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr. 16–18, 04107 Leipzig, Germany; E-Mail:

关键词: microarray;    batch effects;    expression analysis;    quality control;    RNA;   

DOI  :  10.3390/microarrays3040322

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.