Evaluation of DNA microarray results with quantitative gene expression platforms

By R. Canales, Yuling Luo, J. Willey, Bradley Austermiller, Catalin C. Barbacioru, C. Boysen, Kathryn Hunkapiller, R. Jensen, Charles R Knight, Kathleen Y. Lee and 11 more. Nature Biotechnology, 2006

648 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f1c2de5cf87c34618f6d8c038e79d143fd653ba2

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Citations in the corpus

LNCipedia: a database for annotated human lncRNA transcript sequences and structures (2012, methodology): “The performance of the expression array was evaluated using RNA sample titrations according to the MicroArray Quality Control standards (30).”
The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies (2008, methodology): “In the MAQC project, the expression levels of 997 genes randomly selected from available TaqMan® assays have been quantified in the four MAQC samples [13,39].”
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments (2010, methodology): “Here, we evaluate a variety of normalization procedures and focus on two main questions: (1) Does the normalization improve DE detection (sensitivity)? (2) Does the normalization result in low technical variability across replicates (specificity)? To assess DE detection, we rely on the qRT-PCR data ”
Proteomics: Technologies and Their Applications. (2017, methodology): “quantitative proteomics of Bacillus subtilis; Journal of Proteome Research, (2010); 9(7): 3638–3646.”
Direct multiplexed measurement of gene expression with color-coded probe pairs (2008, neutral): “NM_020800 IFT80 226098_at Hs00398803_m1 41 (6) 29 (5) D/D 321 (15) 123 (22) D/D 29.”
PrimerBank: a resource of human and mouse PCR primer pairs for gene expression detection and quantification (2009, methodology): “Quantitative Polymerase Chain Reaction (QPCR) has become a commonly used method for precise determination of gene expression and evaluating DNA microarray data (1,2).”
Estimating accuracy of RNA-Seq and microarrays with proteomics (2009, positive): “Technically, it would allow combining mRNA expression measurements produced by different platforms [3-5].”
Normalization of RNA-seq data using factor analysis of control genes or samples (2014, methodology): “We propose three alternative approaches for estimating the factors of unwanted variation: (i) RUVg uses negative control genes, assumed not to be differentially expressed with respect to the covariates of interest (e.g., ERCC spike-ins); (ii) RUVs uses negative control samples for which the…”
PrimerBank: a PCR primer database for quantitative gene expression analysis, 2012 update (2011, background): “Often the role of qPCR is to validate expression changes of selected genes showing profiles of interest in an initial genome-wide survey (3,4).”
Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms (2008, background): “This is probably due to the absence of background signal and saturation effects, which are major causes of ratio compression on microarrays (39).”
Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data (2013, methodology): “As an additional measure of the accuracy of normalization we correlated the log2 normalized expression changes reported by each method with log expression changes measured by qRT-PCR, which is only available for the MACQ dataset [31].”
The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements (2006, methodology): “Although some data from the alternative platforms are presented in this article, a more thorough discussion is included elsewhere 22 .”
A systems biology approach for pathway level analysis. (2007, background): “While agreeing on the cell cycle, the impact analysis also identifies the three other relevant pathways as significant at the 5% level. to be inhibited in mammary cells microinjected with inhibitors of MAP kinase pathway (Chen et al. 2001).”