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Correlation between  Microarray  and Taqman fold-changes

Journal: BMC Bioinformatics

Article Title: Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

doi: 10.1186/1471-2105-12-413

Figure Lengend Snippet: Correlation between Microarray and Taqman fold-changes

Article Snippet: As our study focuses on the preprocessing of spotted microarray data, we decided to perform analyses on a high density spotted oligonucleotide microarray platform (CodeLink Human Whole Genome from GE Healthcare) as well as on a low density spotted cDNA microarray platform (Dualchip Microarray from Eppendorf).

Techniques: Microarray

Scatter plot between microarray and Taqman . Scatter plot of log2 fold-changes obtained from quantitative PCR versus the log2 fold-changes obtained from microarray after the best- (Standard background correction with log2 transformation) and the worst- (No background correction with glog transformation) preprocessing methods. Microarray data leads to fold-change compressions for many genes, especially with the No background correction and the glog transformation (see Figure2).

Journal: BMC Bioinformatics

Article Title: Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

doi: 10.1186/1471-2105-12-413

Figure Lengend Snippet: Scatter plot between microarray and Taqman . Scatter plot of log2 fold-changes obtained from quantitative PCR versus the log2 fold-changes obtained from microarray after the best- (Standard background correction with log2 transformation) and the worst- (No background correction with glog transformation) preprocessing methods. Microarray data leads to fold-change compressions for many genes, especially with the No background correction and the glog transformation (see Figure2).

Article Snippet: As our study focuses on the preprocessing of spotted microarray data, we decided to perform analyses on a high density spotted oligonucleotide microarray platform (CodeLink Human Whole Genome from GE Healthcare) as well as on a low density spotted cDNA microarray platform (Dualchip Microarray from Eppendorf).

Techniques: Microarray, Real-time Polymerase Chain Reaction, Transformation Assay

GE Healthcare Fold-change compression . Lowess curves of the log2 fold-change compression estimated with the GE Healtchare platform as a function of the average processed intensity. The No background correction as well as the glog transformation produce high fold-change compression at low processed intensities. The fold-change compression at low intensities affects the correlation between gold-standard fold-changes and those obtained with microarray data (see Table 2).

Journal: BMC Bioinformatics

Article Title: Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

doi: 10.1186/1471-2105-12-413

Figure Lengend Snippet: GE Healthcare Fold-change compression . Lowess curves of the log2 fold-change compression estimated with the GE Healtchare platform as a function of the average processed intensity. The No background correction as well as the glog transformation produce high fold-change compression at low processed intensities. The fold-change compression at low intensities affects the correlation between gold-standard fold-changes and those obtained with microarray data (see Table 2).

Article Snippet: As our study focuses on the preprocessing of spotted microarray data, we decided to perform analyses on a high density spotted oligonucleotide microarray platform (CodeLink Human Whole Genome from GE Healthcare) as well as on a low density spotted cDNA microarray platform (Dualchip Microarray from Eppendorf).

Techniques: Transformation Assay, Microarray