Journal ArticleDOI
Microarray data normalization and transformation
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TLDR
This review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.Abstract:
Underlying every microarray experiment is an experimental question that one would like to address. Finding a useful and satisfactory answer relies on careful experimental design and the use of a variety of data-mining tools to explore the relationships between genes or reveal patterns of expression. While other sections of this issue deal with these lofty issues, this review focuses on the much more mundane but indispensable tasks of 'normalizing' data from individual hybridizations to make meaningful comparisons of expression levels, and of 'transforming' them to select genes for further analysis and data mining.read more
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Journal ArticleDOI
Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes
TL;DR: A program, Venn Mapper, is developed to calculate the statistical significance of the number of co-occurring differentially expressed genes in any of the two experiments and suggests that genes expressed higher in stromal cells are also implicated in metastatic prostate cancer and BRCA mutated breast cancer.
Book ChapterDOI
ArrayTrack: An FDA and Public Genomic Tool
Hong Fang,Stephen C. Harris,Zhenjiang Su,Minjun Chen,Feng Qian,Leming Shi,Roger Perkins,Weida Tong +7 more
TL;DR: A public microarray data management and analysis software, called ArrayTrack, that is also used in the routine review of genomic data submitted to the FDA and provides a rich collection of functional information about genes, proteins, and pathways drawn from various public biological databases for facilitating data interpretation.
Journal ArticleDOI
Effect of 30 per cent maternal nutrient restriction from 0.16 to 0.5 gestation on fetal baboon kidney gene expression
Laura A. Cox,Mark J. Nijland,Jeffrey S. Gilbert,Natalia Schlabritz-Loutsevitch,Natalia Schlabritz-Loutsevitch,Gene B. Hubbard,Thomas J. McDonald,Thomas J. McDonald,Robert E. Shade,Peter W. Nathanielsz,Peter W. Nathanielsz +10 more
TL;DR: In this paper, the authors evaluated the specificity of the Affymetrix human gene array for use with fetal baboon mRNA and investigated the effects of moderate maternal global nutrient restriction (NR; 70% of ad libitum animals) from early (30 days gestation (dG)) to mid-gestation (90 dG; term = 184 dG) on the fetal kidney.
Journal ArticleDOI
In control: systematic assessment of microarray performance
TL;DR: It is argued that external RNA controls offer the most versatile system for determining performance and described how such standards could be implemented.
References
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Journal ArticleDOI
Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Book
Data Reduction and Error Analysis for the Physical Sciences
TL;DR: In this paper, Monte Carlo techniques are used to fit dependent and independent variables least squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI
Data Reduction and Error Analysis for the Physical Sciences.
TL;DR: Numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal and Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-square fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Journal ArticleDOI
Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
Book
Regression Analysis by Example
Samprit Chatterjee,B. Price +1 more
TL;DR: Simple linear regression Multiple linear regression Regression Diagnostics: Detection of Model Violations Qualitative Variables as Predictors Transformation of Variables Weighted Least Squares The Problem of Correlated Errors Analysis of Collinear Data Biased Estimation of Regression Coefficients Variable Selection Procedures Logistic Regression Appendix References as discussed by the authors