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For microarray analysis Robust Multichip Analysis (RMA) was performed.
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Consistent with this idea, our microarray analysis showed robust elevation in the expression of genes associated with xenobiotic detoxification pathways.
DM: Diabetes Mellitus; DN: Diabetic Nephropathy; EST: expressed sequence tag; GK: Goto-Kakizaki; IPA: Ingenuity Pathway Analysis; LIMMA: Linear Models for Microarray Analysis; RMA: Robust Multi-array Analysis; STZ: Streptozotocin; WKY: Wistar-Kyoto; QRT-PCR: quantitative real time PCR; TR: transcription ratio.
The microarray analysis provided a robust target gene set that underwent changes in expression due to As3+ exposure, even though the set was below the threshold of significance as determined by statistical analysis.
Our recent microarray analysis pointed to robust changes in the expression of glutamate transporters SLC1A1 and SLC1A3 upon resistance development in both HCT116 cells and LoVo cells (Additional file 1: Figure S1A) [ 13].
Chips were normalized with Robust Microarray Analysis (RMA) in R using Bioconductor.
Preprocessing steps such as background subtraction, probe cell normalization and expression level calculations, were performed using quantile normalization and Robust Microarray Analysis (RMA) software [12].
Robust Microarray Analysis (RMA) and Affymetrix Microarray Suite 5.0 (Mas5) background corrections and normalizations were applied independently to the raw data sets using the Bioconductor open source software [51].
Expression signal values and p-values were obtained for each PS using the Robust Microarray Analysis (RMA) algorithm in ArrayAssit® software (Stratagene, La Jolla, CA, USA), on the "full" PS set (1,381,324 PS).
We compared the temporal expression profile for gata3 derived by Taqman qRT-PCR from the cell line OC-1 with the same samples hybridized to the MU11k GeneChips and analysed with either gMOS, mgMOS, MASv.5 or Robust Microarray Analysis (RMA).
Robust microarray analysis (RMA) was applied for normalization.
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