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
Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics
Stephen J. Callister,Richard C. Barry,Joshua N. Adkins,Ethan T. Johnson,Wei-Jun Qian,Bobbie-Jo M. Webb-Robertson,Richard D. Smith,Mary S. Lipton +7 more
TL;DR: Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS).
Journal ArticleDOI
An insight-based methodology for evaluating bioinformatics visualizations
TL;DR: This paper presents several characteristics of insight that enabled us to recognize and quantify it in open-ended user tests and evaluated five microarray visualization tools on the amount and types of insight they provide and the time it takes to acquire it.
Journal ArticleDOI
A practical guide to linking brain-wide gene expression and neuroimaging data.
TL;DR: It is suggested that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field of brain structure and function.
Journal ArticleDOI
Coordinated activation of metabolic pathways for antioxidants and defence compounds by jasmonates and their roles in stress tolerance in Arabidopsis
Yuko Sasaki-Sekimoto,Nozomi Taki,Takeshi Obayashi,Mitsuko Aono,Fuminori Matsumoto,Nozomu Sakurai,Hideyuki Suzuki,Masami Yokota Hirai,Masaaki Noji,Kazuki Saito,Tatsuru Masuda,Ken-ichiro Takamiya,Daisuke Shibata,Hiroyuki Ohta +13 more
TL;DR: In this paper, a comprehensive analysis of jasmonate-regulated metabolic pathways in Arabidopsis was performed using cDNA macroarrays containing 13516 expressed sequence tags (ESTs) covering 8384 loci.
Journal ArticleDOI
Correlation of Relative Abundance Ratios Derived from Peptide Ion Chromatograms and Spectrum Counting for Quantitative Proteomic Analysis Using Stable Isotope Labeling
TL;DR: It is demonstrated that spectrum counting and mass spectrometry derived ion chromatograms strongly correlate for determining quantitative changes in protein expression and has a wider dynamic range contributing to the deviation of the two quantitative approaches from a perfect positive correlation.
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