Evaluation of gene expression measurements from commercial microarray platforms.
By P. Tan, T. Downey, Edward L. Spitznagel, Pin Xu, Dadin Fu, Dimiter S. Dimitrov, Richard A. Lempicki, B. Raaka, M. Cam. Nucleic Acids Research, 2003
740 citations recorded by the source corpus.
Subfields: Materials Chemistry, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/fa619feb373bebe756f981171452bae4e0439cd1
How researchers see this paper
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In Materials Chemistry
In Molecular Biology
- Balázs Győrffy
- Purvesh Khatri
- Sorin Draghici
- A. Lánczky
- Roger Perkins
- C. Deng
- Tracey Rouault
- Zoltan Szallasi
Citations in the corpus
- A role of SMAD4 in iron metabolism through the positive regulation of hepcidin expression. (2005, methodology): “RNA isolated from the liver of Smad4 Co/Co ;Alb-Cre and wild-type mice at 2 months and 4 months of age was used for microarray based on a procedure described (Tan et al., 2003).”
- PAGE: Parametric Analysis of Gene Set Enrichment (2005, neutral): “While individual microarray studies can be highly informative, it is generally difficult to compare independently obtained data sets addressing the same biological problem [18], regardless of whether the same or different microarray platform was used [19-23].”
- An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients (2010, background): “The use of nearly identical platforms is important since different platforms for geneexpression profiling measure expression of the same gene with varying precision, on different relative scales, and with different dynamic ranges [11].”
- Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients. (2012, background): “The use of almost identical platforms and identical probe sets is vital because different platforms for gene expression profiling measure expression of the same gene with varying accuracy, on different relative scales, and with diverse dynamic ranges (Tan et al. 2003).”
- Comparative Analysis of Proteome and Transcriptome Variation in Mouse (2011, neutral): “[17–21].”
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies (2008, methodology): “[1] found only four common DEGs using an identical set of RNA samples across three popular commercial platforms.”
- FlyAtlas 2: a new version of the Drosophila melanogaster expression atlas with RNA-Seq, miRNA-Seq and sex-specific data (2017, neutral): “Despite the great utility of the FlyAtlas resource, the technology on which it is based––hybridization to Affymetrix microarrays (4)––has limitations: most notably that it does not differentiate between the extent of expression of different mRNA transcripts for the same gene, and that the probe…”
- Reliability and reproducibility issues in DNA microarray measurements. (2006, background): “In a much-cited article, Tan et al. produced gene expression profiles for technical and biological replicates of RNA samples on three different platforms: the oligonucleotide-based CodeLink arrays, Affymetrix Gene-Chips and cDNA arrays from Agilent [ 40 ].”