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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An integrated mBAND and submegabase resolution tiling set (SMRT) CGH array analysis of focal amplification, microdeletions, and ladder structures consistent with breakage-fusion-bridge cycle events in osteosarcoma.
Gloria Lim,Jana Karaskova,Ben Beheshti,Bisera Vukovic,Bisera Vukovic,Jane Bayani,Shamini Selvarajah,Spencer K. Watson,Wan L. Lam,Maria Zielenska,Jeremy A. Squire,Jeremy A. Squire +11 more
TL;DR: Further support is provided for the role of the BFB mechanism and fragile sites in facilitating gene amplification and chromosomal rearrangement in OS.
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Sequential Extracellular Matrix-focused and Baited-global Cluster Analysis of Serial Transcriptomic Profiles Identifies Candidate Modulators of Renal Tubulointerstitial Fibrosis in Murine Adriamycin-induced Nephropathy
Denise M. Sadlier,Susan B. Connolly,Niamh E. Kieran,Sarah A. Roxburgh,Derek P. Brazil,Lukas Kairaitis,Yiping Wang,David Harris,Peter Doran,Hugh R. Brady +9 more
TL;DR: Molecular mechanisms of renal tubulointerstitial fibrosis (TIF) were probed by monitoring changes in the renal transcriptome in a glomerular disease-dependent model of TIF using Affymetrix microarray coupled with sequential primary biological function-focused and secondary “baited”-global cluster analysis of gene expression profiles.
Journal ArticleDOI
Differences in adherence and virulence gene expression between two outbreak strains of enterohaemorrhagic Escherichia coli O157 : H7
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Journal ArticleDOI
Adaptive Evolution of Gene Expression in Drosophila.
Armita Nourmohammad,Joachim Rambeau,Torsten Held,Viera Kovacova,Johannes Berg,Michael Lässig +5 more
TL;DR: Evidence that adaptation dominates the evolution of gene expression levels in flies is presented, and a large group of genes with sex-specific adaptation of expression is identified, which predominantly occurs in males.
Journal ArticleDOI
Quantitative Temporal Viromics of an Inducible HIV-1 Model Yields Insight to Global Host Targets and Phospho-Dynamics Associated with Protein Vpr.
John D. Lapek,Mary K. Lewinski,Jacob M. Wozniak,John C. Guatelli,John C. Guatelli,David Gonzalez +5 more
TL;DR: Current mass spectrometry techniques are applied to define mechanisms of viral protein action by identifying host proteins whose abundance is affected by the accessory protein Vpr and the corresponding modulation of down-stream signaling pathways, specifically those regulated by phosphorylation.
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