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
Microarray data analysis: From hypotheses to conclusions using gene expression data
TL;DR: The emphasis in this paper is on the philosophy behind several statistical issues and on a critical interpretation of microarray related analysis methods.
Journal ArticleDOI
Subnetwork state functions define dysregulated subnetworks in cancer.
TL;DR: This work proposes a combinatorial formulation of coordinate dysregulation and decomposes the resulting objective function to cast the problem as one of identifying subnetwork state functions that are indicative of phenotype, and shows that coordinate Dysregulation of larger subnetworks can be bounded using simple statistics on smaller subnets.
Journal ArticleDOI
A novel scheme to assess factors involved in the reproducibility of DNA-microarray data
Sacha A. F. T. van Hijum,Anne de Jong,Richard J.S. Baerends,Harma Karsens,Naomi E. Kramer,Rasmus Larsen,Chris D. den Hengst,Casper J. Albers,Jan Kok,Oscar P. Kuipers +9 more
TL;DR: Clustering experiments showed that trends can be reliably detected also from (very) lowly expressed genes, and the validation scheme allows determining conditions that could be improved to yield even higher DNA-microarray data quality.
Journal ArticleDOI
Comparative Transcriptome Analysis of Listeria monocytogenes Strains of the Two Major Lineages Reveals Differences in Virulence, Cell Wall, and Stress Response
Patrícia Severino,Olivier Dussurget,Olivier Dussurget,Olivier Dussurget,Ricardo Z. N. Vêncio,Emilie Dumas,Patricia Garrido,Gabriel Padilla,Pascal Piveteau,Jean-Paul Lemaître,Frank Kunst,Philippe Glaser,Carmen Buchrieser +12 more
TL;DR: Different patterns of interaction with host cells and the environment, key factors for host colonization and survival in the environment are suggested, according to Listeria monocytogenes strains.
Journal ArticleDOI
Transcriptional profiling of Actinobacillus pleuropneumoniae under iron-restricted conditions
TL;DR: Transcriptional profiling was used to generate a list of genes showing differential expression during iron restriction, enabling a better understanding of the metabolic changes occurring in response to this stress.
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