Literature DB >> 15920285

Optimal amounts of fluorescent dye improve expression microarray results in tumor specimens.

Ali Naderi1, Ahmed A Ahmed, Yanzhong Wang, James D Brenton, Carlos Caldas.   

Abstract

Expression microarrays have great potential for clinical use but variability of the results represents a challenge for reliable practical application. The amount of fluorescent dye used in microarray experiments is a significant source of variability that has not been systematically studied. Here we demonstrate that the quantity of Cy3 dye affects microarray results performed on tumor specimens. Signal-to-noise ratios and coefficients of variation are significantly improved by increasing Cy3 to 150-180 pmol, but any further increase does not improve the data. In conclusion, optimal amounts of dye reduce variability and improve reliability of expression microarray experiments.

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Year:  2005        PMID: 15920285     DOI: 10.1385/MB:30:2:151

Source DB:  PubMed          Journal:  Mol Biotechnol        ISSN: 1073-6085            Impact factor:   2.695


  9 in total

1.  Evaluation of gene expression measurements from commercial microarray platforms.

Authors:  Paul K Tan; Thomas J Downey; Edward L Spitznagel; Pin Xu; Dadin Fu; Dimiter S Dimitrov; Richard A Lempicki; Bruce M Raaka; Margaret C Cam
Journal:  Nucleic Acids Res       Date:  2003-10-01       Impact factor: 16.971

2.  Are data from different gene expression microarray platforms comparable?

Authors:  Anna-Kaarina Järvinen; Sampsa Hautaniemi; Henrik Edgren; Petri Auvinen; Janna Saarela; Olli-P Kallioniemi; Outi Monni
Journal:  Genomics       Date:  2004-06       Impact factor: 5.736

3.  Global expression profiling of yeast treated with an inhibitor of amino acid biosynthesis, sulfometuron methyl.

Authors:  M H Jia; R A Larossa; J M Lee; A Rafalski; E Derose; G Gonye; Z Xue
Journal:  Physiol Genomics       Date:  2000-08-09       Impact factor: 3.107

4.  Fluorescent labelling of cRNA for microarray applications.

Authors:  Peter A C 't Hoen; Floor de Kort; G J B van Ommen; Johan T den Dunnen
Journal:  Nucleic Acids Res       Date:  2003-03-01       Impact factor: 16.971

5.  Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer.

Authors:  T R Hughes; M Mao; A R Jones; J Burchard; M J Marton; K W Shannon; S M Lefkowitz; M Ziman; J M Schelter; M R Meyer; S Kobayashi; C Davis; H Dai; Y D He; S B Stephaniants; G Cavet; W L Walker; A West; E Coffey; D D Shoemaker; R Stoughton; A P Blanchard; S H Friend; P S Linsley
Journal:  Nat Biotechnol       Date:  2001-04       Impact factor: 54.908

6.  A gene-expression signature as a predictor of survival in breast cancer.

Authors:  Marc J van de Vijver; Yudong D He; Laura J van't Veer; Hongyue Dai; Augustinus A M Hart; Dorien W Voskuil; George J Schreiber; Johannes L Peterse; Chris Roberts; Matthew J Marton; Mark Parrish; Douwe Atsma; Anke Witteveen; Annuska Glas; Leonie Delahaye; Tony van der Velde; Harry Bartelink; Sjoerd Rodenhuis; Emiel T Rutgers; Stephen H Friend; René Bernards
Journal:  N Engl J Med       Date:  2002-12-19       Impact factor: 91.245

7.  Within the fold: assessing differential expression measures and reproducibility in microarray assays.

Authors:  Ivana V Yang; Emily Chen; Jeremy P Hasseman; Wei Liang; Bryan C Frank; Shuibang Wang; Vasily Sharov; Alexander I Saeed; Joseph White; Jerry Li; Norman H Lee; Timothy J Yeatman; John Quackenbush
Journal:  Genome Biol       Date:  2002-10-24       Impact factor: 13.583

8.  Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis.

Authors:  Hongjuan Zhao; Trevor Hastie; Michael L Whitfield; Anne-Lise Børresen-Dale; Stefanie S Jeffrey
Journal:  BMC Genomics       Date:  2002-10-30       Impact factor: 3.969

9.  Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling.

Authors:  Ali Naderi; Ahmed A Ahmed; Nuno L Barbosa-Morais; Samuel Aparicio; James D Brenton; Carlos Caldas
Journal:  BMC Genomics       Date:  2004-01-30       Impact factor: 3.969

  9 in total
  1 in total

1.  A consensus prognostic gene expression classifier for ER positive breast cancer.

Authors:  Andrew E Teschendorff; Ali Naderi; Nuno L Barbosa-Morais; Sarah E Pinder; Ian O Ellis; Sam Aparicio; James D Brenton; Carlos Caldas
Journal:  Genome Biol       Date:  2006-10-31       Impact factor: 13.583

  1 in total

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