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
Comparison of Reliable Reference Genes Following Different Hormone Treatments by Various Algorithms for qRT-PCR Analysis of Metasequoia
Jing-Jing Wang,Jing-Jing Wang,Shuo Han,Shuo Han,Weilun Yin,Weilun Yin,Xinli Xia,Xinli Xia,Chao Liu,Chao Liu +9 more
TL;DR: This study provides a foundation for reference gene normalization when analyzing gene expression in Metasequoia by analyzing the expression stability of 14 candidate reference genes in different tissues and following different hormone treatments.
Journal ArticleDOI
Intelligent system for the analysis of microarray data using principal components and estimation of distribution algorithms
TL;DR: An intelligent system for analyzing microarray data that implements three novel non-exclusive approaches for clustering and biclustering whose aim is to find coherent groups of genes with large between-sample variance, integrated into a web-based platform and tested on two real datasets.
Journal ArticleDOI
Universal mouse reference RNA derived from neonatal mice.
TL;DR: An approach to prepare a large amount of mouse reference RNA from whole neonatal mice is reported, which is simple, quick, reliable, reproducible, and inexpensive.
Journal ArticleDOI
Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies
TL;DR: A thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size and provides some practical guidance for selecting a suitable normalization procedure under different scenarios.
Journal ArticleDOI
Of patterns and pathways: microarray technologies for the analysis of filamentous fungi
TL;DR: An overview of some of the key questions that have been addressed using microarray hybridizations with filamentous fungi, with particular focus on the analysis of co-regulated pathways and physically clustered genes, as well as on the use of microarray data to determine a molecular phenotype.
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