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
Citations
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Journal ArticleDOI
A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors
Bobbie-Jo M. Webb-Robertson,Melissa M. Matzke,Jon M. Jacobs,Joel G. Pounds,Katrina M. Waters +4 more
TL;DR: A novel approach is presented to evaluate normalization strategies, which includes the peptide selection component associated with the derivation of normalization values, which improves the structure of the data without introducing bias into the normalized peak intensities.
Book ChapterDOI
DNA Microarrays in Drug Discovery and Development
TL;DR: DNA microarrays are widely used to address a plethora of scientific questions in the pharmaceutical industry, particularly in drug discovery and development and promises to play a key role in furthering research in a number of fields, as discussed in this chapter.
Journal ArticleDOI
Dye bias correction in dual-labeled cDNA microarray gene expression measurements.
Barry A. Rosenzweig,P. Scott Pine,Olen E. Domon,Suzanne M. Morris,James J. Chen,Frank D. Sistare +5 more
TL;DR: It is found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable and can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision.
Journal ArticleDOI
Profound influence of microarray scanner characteristics on gene expression ratios: analysis and procedure for correction
TL;DR: It is suggested that the PMT voltage should be increased to avoid intensities of the weakest spots below the usable range, allowing the brightest spots to reach the level of saturation.
Journal ArticleDOI
Proteomic Analysis of Stationary Phase in the Marine Bacterium “Candidatus Pelagibacter ubique”
Sarah M Sowell,Angela D. Norbeck,Mary S. Lipton,Carrie D. Nicora,Stephen J. Callister,Richard D. Smith,Douglas F. Barofsky,Stephen J. Giovannoni +7 more
TL;DR: “Ca. Pelagibacter ubique” appears to respond adaptively to stationary phase by increasing the abundance of a suite of proteins that contribute to homeostasis rather than undergoing a major remodeling of its proteome, suggesting a limited response to ambient conditions that deprive it of nutrients for short periods.
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