Next Article in Journal
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Previous Article in Journal
Assessing Agreement between miRNA Microarray Platforms
Article Menu

Export Article

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

Open AccessArticle
Microarrays 2014, 3(4), 322-339; doi:10.3390/microarrays3040322

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

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

Abstract

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
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Microarrays EISSN 2076-3905 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top