Evaluation of the gene-specific dye bias in cDNA microarray experiments

Abstract

Motivation:In cDNA microarray experiments all samples are labeled with either Cy3 or Cy5. Systematic and gene-specific dye bias effects have been observed in dual-color experiments. In contrast to systematic effects which can be corrected by a normalization method, the gene-specific dye bias is not completely suppressed and may alter the conclusions about the differentially expressed genes. Methods: The gene-specific dye bias is taken into account using an analysis of variance model. We propose an index, named label bias index, to measure the gene-specific dye bias. It requires at least two self-self hybridization cDNA microarrays. Results: After lowess normalization we have found that the genespecific dye bias is the major source of experimental variability between replicates. The ratio (R/G) may exceed 2. As a consequence false positive genes may be found in direct comparison without dye-swap. The stability of this artifact and its consequences on gene variance and on direct or indirect comparisons are addressed.

Influenza A Virus Protein PB1-F2 Exacerbates IFN-β Expression of Human Respiratory Epithelial Cells

“…For each channel, the median of the signal intensity was used without background subtraction. Data extraction was processed using Anapuce, an R package for two-color microarray data analysis that is downloadable via CRAN (http://cran.rproject.org) (27,28). Once the dye biases were corrected, data were analyzed to define genes that are differentially expressed between infected and uninfected cells.…”

Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood

“…The Fs statistic is similar to the F2, but uses the heterogeneity of the error estimates to inform the exact weighting of the average. As a fifth measure, the R/VarMixt package (Delmar et al, 2005) was used to model residual error as a mixture of different sub-populations of genes, as employed by Martin-Magniette et al (2005) in their earlier assessment of GSDB (see Section 1). In each of these five cases, a fixed ANOVA model was employed using the factors Array, Dye and Sample.…”

Comparative analysis of seed transcriptomes of ambient ozone-fumigated 2 different rice cultivars

“…26 The flip labeling (dye-swap or reverse labeling with Cy3 and Cy5 dyes) procedure was used to nullify the dye bias associated with unequal incorporation of the 2 Cy dyes into cRNA. [48][49][50] The dye-swap approach, which is well established in our laboratories and research, 23,25,26,[51][52][53][54][55] provides a more stringent selection condition for profiling differentially expressed genes rather than simply doing only 2 or 3 replicates, which overlook the dye bias.…”