ArticleBMC genomics2004
Performance evaluation of commercial short-oligonucleotide microarrays and the impact of noise in making cross-platform correlations.
Article in BMC genomics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
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- Social stress increases expression of hemoglobin genes in mouse prefrontal cortex.BMC neuroscience · 2014Article
- Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.BMC genomics · 2014Article
- Current approaches to micro-RNA analysis and target gene prediction.Journal of applied genetics · 2012Review
- Quantitative analysis of microRNAs in tissue microarrays by in situ hybridization.BioTechniques · 2012Article
- Gene expression signatures differ with extent of atherosclerosis in monkey iliac artery.Menopause (New York, N.Y.) · 2011Article
- Quantitative miRNA expression analysis using fluidigm microfluidics dynamic arrays.BMC genomics · 2011Article
- Translating tumor biology into personalized treatment planning: analytical performance characteristics of the Oncotype DX Colon Cancer Assay.BMC cancer · 2010Article
- Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.BMC genomics · 2010Article
- Reciprocal communication between endometrial stromal cells and macrophages.Reproductive sciences (Thousand Oaks, Calif.) · 2010Article
- Detection call algorithms for high-throughput gene expression microarray data.Briefings in bioinformatics · 2010Review
- Regulation of gene expression in brain tissues of rats repeatedly treated by the highly abused opioid agonist, oxycodone: microarray profiling and gene mapping analysis.Drug metabolism and disposition: the biological fate of chemicals · 2010Article
- An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays.BMC bioinformatics · 2009Article
- WebArrayDB: cross-platform microarray data analysis and public data repository.Bioinformatics (Oxford, England) · 2009Article
- Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis.BMC genomics · 2009Article
- Platform dependence of inference on gene-wise and gene-set involvement in human lung development.BMC bioinformatics · 2009Article
- Use of Bayesian networks to probabilistically model and improve the likelihood of validation of microarray findings by RT-PCR.Journal of biomedical informatics · 2009Article
- Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes.BMC genomics · 2009Article
- Gene expression profiling in the aging ovary.Methods in molecular biology (Clifton, N.J.) · 2009Article
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7 authors.
Funding
Abstract
backgroundDespite the widespread use of microarrays, much ambiguity regarding data analysis, interpretation and correlation of the different technologies exists. There is a considerable amount of interest in correlating results obtained between different microarray platforms. To date, only a few cross-platform evaluations have been published and unfortunately, no guidelines have been established on the best methods of making such correlations. To address this issue we conducted a thorough evaluation of two commercial microarray platforms to determine an appropriate methodology for making cross-platform correlations.
resultsIn this study, expression measurements for 10,763 genes uniquely represented on Affymetrix U133A/B GeneChips and Amersham CodeLink UniSet Human 20 K microarrays were compared. For each microarray platform, five technical replicates, derived from the same total RNA samples, were labeled, hybridized, and quantified according to each manufacturers' standard protocols. The correlation coefficient (r) of differential expression ratios for the entire set of 10,763 overlapping genes was 0.62 between platforms. However, the correlation improved significantly (r = 0.79) when genes within noise were excluded. In addition to levels of inter-platform correlation, we evaluated precision, statistical-significance profiles, power, and noise levels for each microarray platform. Accuracy of differential expression was measured against real-time PCR for 25 genes and both platforms correlated well with r values of 0.92 and 0.79 for CodeLink and GeneChip, respectively.
conclusionsAs a result of this study, we recommend using only genes called 'present' in cross-platform correlations. However, as in this study, a large number of genes may be lost from the correlation due to differing levels of noise between platforms. This is an important consideration given the apparent difference in sensitivity of the two platforms. Data from microarray analysis need to be interpreted cautiously and therefore, we provide guidelines for making cross-platform correlations. In all, this study represents the most comprehensive and specifically designed comparison of short-oligonucleotide microarray platforms to date using the largest set of overlapping genes.
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