Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation

@inproceedings{Richard2014ComparisonOG,
  title={Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation},
  author={Arianne C Richard and Paul A. Lyons and James E. Peters and Daniele Biasci and Shaun M Flint and James C. Lee and Eoin F. McKinney and Richard M Siegel and Kenneth G C Smith},
  booktitle={BMC Genomics},
  year={2014}
}
Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack… CONTINUE READING