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
Normalization benefits microarray-based classification
Jianping Hua,Yoganand Balagurunathan,Yi Chen,James Lowey,Michael L. Bittner,Zixiang Xiong,Edward Suh,Edward R. Dougherty +7 more
TL;DR: The conclusion from the different experiment models considered in the study is that normalization can have a significant benefit for classification under difficult experimental conditions, with linear and Lowess regression slightly outperforming the offset method.
Journal ArticleDOI
PreP+07: improvements of a user friendly tool to preprocess and analyse microarray data
TL;DR: Its reliability has been proven so that a laboratory researcher can afford a statistical pre-processing of his/her microarray results and obtain a list of differentially expressed genes using PreP+, without any programming skills.
Journal ArticleDOI
Immune response to influenza vaccination in the elderly is altered by chronic medication use.
Divyansh Agarwal,Kenneth E. Schmader,Andrew V. Kossenkov,Susan A. Doyle,Raj K. Kurupati,Hildegund C.J. Ertl +5 more
TL;DR: Novel pathways that might underlie how long-term medication use impacts immune response to influenza vaccination in the elderly are suggested and provide a strong rationale for targeting the medication-immunity interaction in the aged population to improve vaccination responses.
Journal ArticleDOI
A zebrafish model of PINK1 deficiency reveals key pathway dysfunction including HIF signaling
TL;DR: The findings suggest that a lack of pink1 in zebrafish alters many vital and critical pathways in addition to the HIF signaling pathway.
Gene expression profiling using mixed models
Greg Gibson,Russell D. Wolfinger +1 more
TL;DR: In this paper, both classic and Bayesian approaches are discussed, with a focus on genetic parameter estimation and gene mapping, and an especially nice feature, and indeed worth the price of the book by themselves, are chapters discussing important, but underappreciated, approaches for AMMI modeling of genotype-environment interactions, the analysis of longitudinal traits, and empirical Bayes estimates.
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