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Nuria Lopez-Bigas

BCO17. Methods and tools in functional genomics (microarrays). Nuria Lopez-Bigas. What are microarrays?. What are microarrays?. Microarray data analysis.

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Nuria Lopez-Bigas

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  1. BCO17 Methods and tools in functional genomics (microarrays) Nuria Lopez-Bigas

  2. What are microarrays?

  3. What are microarrays?

  4. Microarray data analysis Microarray data analysis is the step that will allow us to extract biological meaning to high-throughput data generated with the experiment.

  5. Data preprocession and normalization Normalized data Microarray data analysis Microarray DATA

  6. Microarray data analysis Normalization and Noise: Normalization • Some kind of normalization is usually required when comparing more than one microarray experiment. • Adjust to account for differences in overall brightness of slides • Normalize relative to housekeeping genes   Noise • Refers to variability and reproducibility of microarray experiments • Intra and inter-microarray variations can significantly skew interpretation of data • Sample collection is very important.  If comparing two conditions you must control for all variables other than the one you are trying to measure • Technical noise can result from imperfections in the chip. • Both biological and technical replicates are required to measure and control these sources of noise

  7. Data preprocession and normalization Normalized data Microarray DATA Differential expression Data analysis Microarray data analysis

  8. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Data analysis Microarray data analysis

  9. Gene Ontology http://www.geneontology.org The Gene Ontology project provides a controlled vocabulary to describe gene and gene product attributes in any organism. • The Ontologies • Cellular component • Biological process • Molecular function BROWSER::AMIGO TOOLS

  10. Gene Ontology

  11. Gene Ontology

  12. Gene Ontology::Tools http://www.geneontology.org/GO.tools.shtml http://www.fatigo.org/ FUNC-EXPRESSION http://www.barleybase.org/funcexpression.php http://discover.nci.nih.gov/gominer/htgm.jsp

  13. KEGG http://www.genome.jp/kegg/

  14. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Classification Data analysis Microarray data analysis

  15. Classification Support vectors machines Desition trees

  16. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Classification Data analysis Clustering Microarray data analysis

  17. Clustering & Classification Supervised versus Unsupervised: Supervised • Analysis to determine genes that fit a predetermined pattern • Usually used to find genes with expression levels that are significantly different between groups of samples or finding genes that accurately predict a characteristic of the sample • Two popular supervised techniques would be nearest-neighbour analysis and support vector machines.   Unsupervised • Analysis to characterize the components of a data set without a priori input or knowledge of a training signal • Try to find internal structure or relationships in data without trying to predict some ‘correct answer’. • Three classes: 1. Feature determination: Look for genes with interesting patterns Eg. Principal-components analysis 2. Cluster determination: Determine groups of genes with similar expression patterns eg. Nearest-neighbour clustering, self-organizing maps, k-means clustering, 2d hierarchical clustering 3. Network determination: Determine graphs representing gene-gene or gene-phenotype interactions. Eg. Boolean networks, Bayesian networks, relevance networks

  18. Clustering & Classification Cooper Breast Cancer Res 2001 3:158

  19. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Classification Data analysis Clustering Promoter analysis Microarray data analysis

  20. Promoter analysis::TFBS TRANSFAC

  21. Promoter analysis::Tools http://www.cisreg.ca/

  22. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Classification Data analysis Clustering Promoter analysis Reverse engineering Microarray data analysis

  23. Reverse engineering

  24. Data preprocession and normalization Normalized data Microarray DATA Differential expression GO,KEGG…analysis Classification Data analysis Clustering Promoter analysis Reverse engineering Microarray data analysis

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