Statistical design of reverse dye microarrays

Dobbin, Kevin K.; Shih, Joanna H.; Simon, Richard

doi:10.1093/bioinformatics/btg076

Cited by 101 publications

(65 citation statements)

References 27 publications

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“…Application of existing mathematical and graphical tools from these three areas requires the inclusion of internal validation datasets (i.e. repeated measures in statistical parlance), such as self-self hybridizations, spiked-in controls and reference sample designs, which are becoming increasingly common (58,59). …”

Section: Discussionmentioning

confidence: 99%

Operational criteria for selecting a cDNA microarray data normalization algorithm

Argyropoulos

Chatziioannou²,

Nikiforidis³

et al. 2006

Oncol Rep

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Abstract. Microarray technology allows gene expression profiling at a global level. Many algorithms for the normalization of raw microarray data have been proposed, but no attempt has yet been made to propose operationally verifiable criteria for their comparative evaluation, which is necessary for the selection of the most appropriate method for a given dataset. This study develops a set of operational criteria for assessing the impact of various normalization algorithms in terms of accuracy (bias), precision (variance) and over-fitting (information reduction). The use of these criteria is illustrated by applying the three most widely used algorithms (global median normalization, spiked-in based normalization and lowess) on a specifically designed, multiply-controlled dataset.

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Section: Discussionmentioning

confidence: 99%

Operational criteria for selecting a cDNA microarray data normalization algorithm

Argyropoulos

Chatziioannou²,

Nikiforidis³

et al. 2006

Oncol Rep

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“…Removal of this variable dye bias is important to obtain a more accurate set of statistically significant microarray data to enhance confidence in interpretation of the biological effects of the test agent. Many labs perform dye reversal or dye-swap experiments in which two microarray hybridizations are performed for each given dose and time data point, alternating the labeling of each treated and control sample with the Cy3 and Cy5 dyes (Dobbin et al 2003;Yang et al 2001). The microarray results are then averaged between the dye-swap pair, eliminating the dye-bias artifact.…”

Section: Discussionmentioning

confidence: 99%

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

Rosenzweig

Pine

Domon

et al. 2004

Environ Health Perspect

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A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to genespecific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias.

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“…En el proceso de hibridación de las micromatrices, los mRNAs de la planta infectada y de la planta sana se marcan con dos fluoróforos diferentes (CY3 y CY5), pero se ha observado que algunos mRNAs se unen a ambos fluoróforos con distinta eficiencia (Dobbin et al, 2003). Para evitar errores derivados de este efecto se utilizó un diseño Dye-Swap, en el que se marcaron los mRNAs de cada planta con un fluoróforo diferente en cada hibridación.…”

Section: Diseño Experimentalunclassified

Estudio de la interacción entre naranjo amargo y el virus de la tristeza de los cítricos

Serra¹

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Statistical design of reverse dye microarrays

Cited by 101 publications

References 27 publications

Operational criteria for selecting a cDNA microarray data normalization algorithm

Operational criteria for selecting a cDNA microarray data normalization algorithm

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

Estudio de la interacción entre naranjo amargo y el virus de la tristeza de los cítricos

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