Microarray experiments and factors which affect their reliability

Roman Jaksik*, Marta Iwanaszko, Joanna Rzeszowska-Wolny, Marek Kimmel

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

94 Scopus citations

Abstract

Oligonucleotide microarrays belong to the basic tools of molecular biology and allow for simultaneous assessment of the expression level of thousands of genes. Analysis of microarray data is however very complex, requiring sophisticated methods to control for various factors that are inherent to the procedures used. In this article we describe the individual steps of a microarray experiment, highlighting important elements and factors that may affect the processes involved and that influence the interpretation of the results. Additionally, we describe methods that can be used to estimate the influence of these factors, and to control the way in which they affect the expression estimates. A comprehensive understanding of the experimental protocol used in a microarray experiment aids the interpretation of the obtained results. By describing known factors which affect expression estimates this article provides guidelines for appropriate quality control and pre-processing of the data, additionally applicable to other transcriptome analysis methods that utilize similar sample handling protocols. Reviewers: This article was reviewed by Dr. Janet Siefert, Dr. Leonid Hanin, and Dr. I King Jordan.

Original languageEnglish (US)
Article number46
JournalBiology Direct
Volume10
Issue number1
DOIs
StatePublished - Sep 3 2015

Funding

We thank Ron Hancock, Anna Lalik and Robert Herok for very helpful discussions. This work was supported by Polish National Science Center grant DEC-2012/04/ A/ST7/00353 (RJ, JR and MK) and POIG.02.03.01-00-040/13 (MI).

Keywords

  • Measurement bias
  • Microarray pre-processing
  • Microarrays
  • Quality control
  • Transcriptome profiling

ASJC Scopus subject areas

  • Immunology
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • Applied Mathematics

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