Normalization for cDNA microarry data

By Y. H. Yang, Sandrine Dudoit, Percy Luu, Terence P. Speed. SPIE BiOS, 2001

437 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/88c1d2d6fc5eafc5a4acf40db258844b56d17301

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In Molecular Biology

Citations in the corpus

Bayesian infinite mixture model based clustering of gene expression profiles (2002, background): “Typically, in the process of normalizing microarray data, an attempt is made to remove systematic correlations that can occur due to the microarrayto-microarray variability that systematically affects all genes on the microarray (Yang et al., 2001).”
Use of within-array replicate spots for assessing differential expression in microarray experiments (2005, methodology): “Foreground intensities were background corrected using the ‘morph’ background measure and the scorecard spot log-ratios were normalized using global loess normalization with the default smoothing span of 0.3 (Yang et al., 2001; Smyth and Speed, 2003).”
Analysis of array CGH data: from signal ratio to gain and loss of DNA regions (2004, background): “In practice, microarray experiments are subject to various sources of variation, including differences in incorporation efficiency between the two fluorescent dyes, an intensity-dependent effect and a print-tip effect, as reported by Yang et al. (2001) for expression data.”
STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS (2002, background): “In other circumstances, a subset of control sequences may be spotted on the slide and used for normalization purposes (see Yang et al. (2001) for greater detail on normalization).”
Multiple Hypothesis Testing in Microarray Experiments (2003, methodology): “The raw data in a microarray experiment consist of image files, and important preprocessing steps include image analysis of these scanned images and normalization (Yang et al., 2001, 2002).”
A comparison of background correction methods for two-colour microarrays (2007, methodology): “Avoiding background correction altogether is recommended by Yang et al. (2001a) and Tran et al. (2002).”
Controlling the number of false discoveries: application to high-dimensional genomic data (2004, methodology): “We note that recent statistical work has described more complex alternatives to median normalization to normalize gene expression data (Yang et al., 2001; Chen et al., 1997).”