Literature DB >> 14988009

Gene-specific dye bias in microarray reference designs.

Alan A Dombkowski1, Bryan J Thibodeau, Susan L Starcevic, Raymond F Novak.   

Abstract

The most widely used microarray experiment design includes the use of a reference standard. Comparisons of gene expression between samples are facilitated because each sample is directly measured against the reference standard, using two fluorescent dyes. Numerous reports indicate that some genes incorporate the two commonly used dyes with different efficiencies, contributing to inaccurate data. However, it is widely assumed that these effects will not corrupt results if the reference standard is labeled with the same dye on each microarray. We demonstrate that this assumption is not reliable and that dye orientation can significantly influence measured changes in gene expression.

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Year:  2004        PMID: 14988009     DOI: 10.1016/S0014-5793(04)00083-3

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  12 in total

Review 1.  A review of statistical methods for expression quantitative trait loci mapping.

Authors:  Christina Kendziorski; Ping Wang
Journal:  Mamm Genome       Date:  2006-06-12       Impact factor: 2.957

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

Authors:  Ryan Kelley; Hoda Feizi; Trey Ideker
Journal:  Bioinformatics       Date:  2007-07-10       Impact factor: 6.937

3.  Sequence-dependent fluorescence of cyanine dyes on microarrays.

Authors:  Christy Agbavwe; Mark M Somoza
Journal:  PLoS One       Date:  2011-07-25       Impact factor: 3.240

4.  Application of four dyes in gene expression analyses by microarrays.

Authors:  Yvonne C M Staal; Marcel H M van Herwijnen; Frederik J van Schooten; Joost H M van Delft
Journal:  BMC Genomics       Date:  2005-07-25       Impact factor: 3.969

5.  SIMAGE: simulation of DNA-microarray gene expression data.

Authors:  Casper J Albers; Ritsert C Jansen; Jan Kok; Oscar P Kuipers; Sacha Aft van Hijum
Journal:  BMC Bioinformatics       Date:  2006-04-13       Impact factor: 3.169

6.  A generally applicable validation scheme for the assessment of factors involved in reproducibility and quality of DNA-microarray data.

Authors:  Sacha A F T van Hijum; Anne de Jong; Richard J S Baerends; Harma A Karsens; Naomi E Kramer; Rasmus Larsen; Chris D den Hengst; Casper J Albers; Jan Kok; Oscar P Kuipers
Journal:  BMC Genomics       Date:  2005-05-20       Impact factor: 3.969

7.  Changes in brain MicroRNAs contribute to cholinergic stress reactions.

Authors:  Ari Meerson; Luisa Cacheaux; Ki Ann Goosens; Robert M Sapolsky; Hermona Soreq; Daniela Kaufer
Journal:  J Mol Neurosci       Date:  2009-08-27       Impact factor: 3.444

8.  Adaptable gene-specific dye bias correction for two-channel DNA microarrays.

Authors:  Thanasis Margaritis; Philip Lijnzaad; Dik van Leenen; Diane Bouwmeester; Patrick Kemmeren; Sander R van Hooff; Frank C P Holstege
Journal:  Mol Syst Biol       Date:  2009-04-28       Impact factor: 11.429

9.  Pre-processing Agilent microarray data.

Authors:  Marianna Zahurak; Giovanni Parmigiani; Wayne Yu; Robert B Scharpf; David Berman; Edward Schaeffer; Shabana Shabbeer; Leslie Cope
Journal:  BMC Bioinformatics       Date:  2007-05-01       Impact factor: 3.169

10.  Assessing probe-specific dye and slide biases in two-color microarray data.

Authors:  Ruixiao Lu; Geun-Cheol Lee; Michael Shultz; Chris Dardick; Kihong Jung; Jirapa Phetsom; Yi Jia; Robert H Rice; Zelanna Goldberg; Patrick S Schnable; Pamela Ronald; David M Rocke
Journal:  BMC Bioinformatics       Date:  2008-07-19       Impact factor: 3.169

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