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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Genome-wide analysis of the interaction between the endosymbiotic bacterium Wolbachia and its Drosophila host
TL;DR: In vivo characterization of differentially-expressed products in gonads demonstrates that Angiotensin Converting Enzyme varies between Wolbachia infected and uninfected flies and that the variation occurs in a sex-specific manner, which supports the use of Wolbachian infected cell cultures as an appropriate model for predicting in vivo host/Wolbachia interactions.
Journal ArticleDOI
DAnTE: a statistical tool for quantitative analysis of -omics data
Ashoka D. Polpitiya,Wei-Jun Qian,Navdeep Jaitly,Vladislav A. Petyuk,Joshua N. Adkins,David G. Camp,Gordon A. Anderson,Richard D. Smith +7 more
TL;DR: DAnTE features selected normalization methods, missing value imputation algorithms, peptide-to-protein rollup methods, an extensive array of plotting functions and a comprehensive hypothesis-testing scheme that can handle unbalanced data and random effects.
Journal ArticleDOI
Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes
Chao-Gan Yan,R. Cameron Craddock,R. Cameron Craddock,Xi-Nian Zuo,Yu-Feng Zang,Michael P. Milham,Michael P. Milham +6 more
TL;DR: The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common fMRI measures and nuisance variables, as well as phenotypic variables of interest.
Journal ArticleDOI
Glucocorticoids induce differentiation of a specifically activated, anti-inflammatory subtype of human monocytes.
Jan Ehrchen,Lars Steinmüller,Katarzyna Barczyk,Klaus Tenbrock,Wolfgang Nacken,Martin Eisenacher,Ursula Nordhues,Clemens Sorg,Cord Sunderkötter,Johannes Roth +9 more
TL;DR: GC treatment did not cause a global suppression of monocytic effector functions but results in differentiation of a specific anti-inflammatory phenotype which seems to be actively involved in resolution of inflammatory reactions.
Journal ArticleDOI
Fundamentals of cDNA microarray data analysis
Yuk Fai Leung,Duccio Cavalieri +1 more
TL;DR: An overview of the contemporary trend on various main analysis steps in the microarray data analysis process, which includes experimental design, data standardization, image acquisition and analysis, normalization, statistical significance inference, exploratory data analysis, class prediction and pathway analysis, as well as various considerations relevant to their implementation.
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