Variance stabilization applied to microarray data calibration and to the quantification of differential expression

By Wolfgang Huber, Anja von Heydebreck, H. Sültmann, A. Poustka, Martin Vingron. Intelligent Systems in Molecular Biology, 2002

2,594 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4df1ee2955b90258c8aeb25d032c71c4c21e042f

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Citations in the corpus

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 (2014, neutral): “Alternative estimators can be found which are more stable than the standard calculation of fold change as the ratio of average observed values for each condition [52, 53, 54].”
A global test for groups of genes: testing association with a clinical outcome (2004, methodology): “Normalization on the 12 samples was carried out using the variance stabilizing method VSN (Huber et al., 2002).”
Unidirectional transfer of microRNA-loaded exosomes from T cells to antigen-presenting cells (2011, methodology): “Statistical analysis Microarray data were normalized by the variance stabilization normalization (VSN) metho”
Chipster: user-friendly analysis software for microarray and other high-throughput data (2011, methodology): “The actual normalization methods, such as Robust Multi-array Average (RMA), Li-Wong (dChip), loess, quantile, robust spline and variance stabilizing normalization, are implemented as parameters of the tools [11,12].”
Ten quick tips for effective dimensionality reduction (2019, neutral): “Examples of supervised DR methods include partial least squares (PLS) [17], linear discriminant analysis (LDA) [18], neighborhood component analysis (NCA) [19], and the bottleneck neural network classifier [20].”
Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses (2012, methodology): “Gene expression normalization and the necessary preprocessing of genotype information need to be done using external tools 25,26 .”
A comparison of background correction methods for two-colour microarrays (2007, methodology): “Kooperberg et al. (2002) gives an empirical Bayes model to estimate the true signal.”
A Model-Based Background Adjustment for Oligonucleotide Expression Arrays (2004, neutral): “Durbin et al. (2002), Huber et al. (2002), Cui, Kerr, and Churchill (2003), and Irizarry et al. (2003a) have proposed additive-background-multiplicative-measurement-error (ABME) models for intensities read from microarray scanners.”
Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity (2014, positive): “, 2011) containing genomewide RNA-seq variance-stabilized expression levels (Huber et al., 2002) taken from 19 strains of seedling Arabidopsis thaliana and matching genome sequences.”
Reference Maps of Human ES and iPS Cell Variation Enable High-Throughput Characterization of Pluripotent Cell Lines (2011, positive): “We tested several different procedures and found that a combination of spike-in normalization using positive controls and the VSN algorithm (Huber et al., 2002) produced best results.”
MicroRNA expression alterations are linked to tumorigenesis and non-neoplastic processes in pancreatic ductal adenocarcinoma (2007, methodology): “The raw array data were normalized with the VSN method (Huber et al., 2002).”