ArticleBMC genomics2009
Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes.
Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A novel tissue-specific meta-analysis approach for gene expression predictions, initiated with a mammalian gene expression testis database.BMC genomics · 2010Pooled it
- Pooled it
- Conserved properties of genetic architecture of renal and fat transcriptomes in rat models of insulin resistance.Disease models & mechanisms · 2019Article
- Combined analysis and validation for DNA methylation and gene expression profiles associated with prostate cancer.Cancer cell international · 2019Article
- Adaptive expression of microRNA-125a in adipose tissue in response to obesity in mice and men.PloS one · 2014Article
- Article
- Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data.BMC bioinformatics · 2013Article
- Article
- Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3.BMC genomics · 2010Article
- MicroRNA-125a is over-expressed in insulin target tissues in a spontaneous rat model of Type 2 Diabetes.BMC medical genomics · 2009Article
- Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus.BMC medical genomics · 2009Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundMicroarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms.
resultsWe present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms.
conclusionThis study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.
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