Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

By Y. H. Yang, Sandrine Dudoit, Percy Luu, Dave Lin, V. Peng, John Ngai, Terence P. Speed. Nucleic Acids Research, 2002

3,676 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2c9ea0c1487a355694264689b304a700015cd55e

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Citations in the corpus

Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatment (2004, positive): “Each channel of data in a pair of dye-swapping hybridizations was normalized by means of LOWESS [3] method.”
Early dissemination seeds metastasis in breast cancer (2016, positive): “To avoid smoothing true focal alterations, the weight of probes with an absolute log ratio deviation greater than 0.5 from the piecewise constant function were set to zero for the Loess fit.”
limma powers differential expression analyses for RNA-sequencing and microarray studies (2015, methodology): “A popular method is to remove intensity-dependent dye-biases and spatial artefacts from M -values (log-intensity ratios) using locally weighted regression (loess) (35).”
Arabidopsis CBF3/DREB1A and ABF3 in Transgenic Rice Increased Tolerance to Abiotic Stress without Stunting Growth1[w] (2005, methodology): “Block-by-block Lowess normalization (Yang et al., 2002) and multivariate statistics such as clustering, principal component analysis, multidimensional scaling, etc. were analyzed with Acuity 3.1 (Axon Instruments).”
Design issues for cDNA microarray experiments (2002, background): “2 ), in which each hybridization is done twice, with the dye assignments reversed in the second hybridization, are useful for reducing systematic bia”
Comparative Genomics in Salt Tolerance between Arabidopsis and Arabidopsis-Related Halophyte Salt Cress Using Arabidopsis Microarray1 (2004, methodology): “Intensitydependent normalization (Yang et al., 2002) was used to equalize hybridization signals generated from different samples.”
Normalization of cDNA microarray data. (2003, neutral): “This method was compared with ordinary print-tip loess normalization by Yang et al [5].”
Analysis of microarray data using Z score transformation. (2003, neutral): “Traditional ratio calculations of significant changes in gene expression derived from globally normalized data are performed by simply computing the ratio of the average of all of the measurements from one condition or sample to another.(4) Significance is customarily assigned to genes whose ratio i”
Evaluation of gene expression measurements from commercial microarray platforms. (2003, methodology): “1) were used, which selects the LOWESS (locally weighted linear regression curve ®t) normalization method (6).”
Cyclic mononucleotide- and Clr-dependent gene regulation in Sinorhizobium meliloti. (2016, methodology): “A normalization method based on local regression that accounts for intensity and spatial dependence in dye biases was used (Yang et al., 2002).”