Another preliminary, but important, finding of this study is that molecular signatures might be generalized to populations other than those in which they were initially developed, and across multiple microarray platforms and technologies.
Previous studies investigating large-scale changes in gene expression in primates in multiple tissues employed microarray technologies (Caceres et al. 2003; Gu J and Gu X 2003; Karaman et al. 2003; Khaitovich et al. 2004, 2005, 2006a; Uddin et al. 2004; Gilad et al. 2005, 2006; Blekhman et al. 2008; Somel et al. 2009).
The Affymetrix GeneChip® gene expression analysis array, one of most commonly used microarray technologies, uses multiple oligonuleotides (25-mers) to measure expression abundance of a single gene.
Several studies have used samples from biological tissue to compare multiple microarray platforms with other measurement technologies, either mixing RNA from two tissues at known ratios [ 21] or harvesting RNA in stimulated and unstimulated conditions [ 22, 23].
This review outlines multiple aspects of microarray technology and highlights some of the benefits, limitations and also pitfalls of the technique.
Here we report the first comparative analyses of multiple gene transcription data sets obtained in parallel with different microarray technologies over several popular normalisation methods using multiple cross-platform concordance criteria.
Since the development of multiple and simultaneous measurement techniques such as microarray technologies, reverse engineering of biochemical and, in particular, gene regulatory networks has become a more important problem in systems biology.
Moreover, in the specific case of microarray technologies, given the large numbers of statistical tests conducted, it is usually required to correct for multiple comparisons.
Bubendorf, L. High-throughput microarray technologies: from genomics to clinics.
A scalable method for integration and functional analysis of multiple microarray datasets.
