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
Use of Microarray Technology to Profile Gene Expression Patterns Important for Reproduction in Cattle
TL;DR: This review focuses on the types of microarrays available for studies in cattle and concludes that genes associated with one or more of the cellular processes of cell survival/death, intracellular signalling, transcription and translation, cell division and proliferation and cellular metabolism are the main transcriptional pathways that control the development of ovarian follicles, oocytes, early embryos and the uterine endometrium about the time of the establishment of pregnancy.
Journal ArticleDOI
A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis.
Junfeng Chen,Vikas Agrawal,Magnus Rattray,Marilyn A. L. West,Dina A. St. Clair,Richard W Michelmore,Sean J. Coughlan,Blake C. Meyers +7 more
TL;DR: Comparisons of transcript expression ratios showed greater consistency across platforms than measurements of transcript abundance, which suggests that technology differences can mask the impact of biological differences between samples and tissues.
Journal ArticleDOI
Strong position-dependent effects of sequence mismatches on signal ratios measured using long oligonucleotide microarrays
TL;DR: This study describes a large-scale investigation of microarray hybridisations to murine probes with known sequence mismatches, demonstrating that the effect of mismatches is strongly position-dependent and for small numbers of sequence mismatch is correlated with the maximum length of perfectly matched probe-target duplex.
Hierarchical Clustering with CUDA/GPU.
TL;DR: This work explores parallel computation of hierarchical clustering with CUDA/GPU, and obtains an overall speed-up of up to 48 times over sequential computation with an Intel Pentium CPU.
Journal ArticleDOI
Toxicogenomics in the assessment of immunotoxicity
Kirsten A. Baken,Rob J. Vandebriel,Jeroen L. A. Pennings,Jos C. S. Kleinjans,Henk Van Loveren +4 more
TL;DR: The examples of assessment of immunotoxicity by gene expression profiling presented and discussed here, show that microarray analysis is able to detect known and novel effects of a wide range of immunomodulating agents.
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