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PATHWAY ANALYSIS

PATHWAY ANALYSIS. Susan LM Coort, PhD Department of Bioinformatics, Maastricht University susan.coort@maastrichtuniversity.nl. Data analysis overview. Slide based on a slide from J. Pennings, RIVM, NL. Microarray scans. Image analysis. Arrayanalysis.org. Raw data. Quality control

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PATHWAY ANALYSIS

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  1. PATHWAY ANALYSIS Susan LM Coort, PhD Department of Bioinformatics, Maastricht University susan.coort@maastrichtuniversity.nl PET course: Toxicogenomics

  2. Data analysis overview Slide based on a slide from J. Pennings, RIVM, NL Microarray scans Image analysis Arrayanalysis.org Raw data Quality control Normalization Preprocessing NuGOexprFileCreator Normalized data Limma (GP) Statistical analysis ANOVA (AT) List of regulated genes Pattern analysis Gene ontology analysis Promoter analysis Textmining Pathway analysis Clustering (AT) GO-Elite oPOSSUM CoPub Untreated (control) Exposed to compound Results

  3. Understanding microArray data • Typical procedure • Annotate the reporters with something useful (like Entrezgene) PET course: Toxicogenomics

  4. Identifiers Identifier (id) for probe on microarray (example -> Cyp1A1): Platform specific id: Affymetrix id: 205749_at Agilent id: A_14_P106416 Illumina id: ILMN_4380 • General gene id: • Entrez Gene id: 1543 • Ensembl id: ENSG00000140465 • Refseq id: NM_000494 PET course: Toxicogenomics

  5. Entrez Gene Identifier PET course: Toxicogenomics

  6. Ensembl Identifier PET course: Toxicogenomics

  7. Refseq identifier PET course: Toxicogenomics

  8. Protein identifiers -> UniProt id PET course: Toxicogenomics

  9. Find information on genes in databases on internet: NetAffx: search with Affymetrix id SOURCE: search with Entrez Gene id, Ensembl id (rat, mouse, human) DAVID: linking gene databases Annotation (I) PET course: Toxicogenomics

  10. CYP PET course: Toxicogenomics

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  14. Understanding microArray data • Typical procedure • Annotate the reporters with something useful (like Entrezgene) • Sort based on fold change and p-value PET course: Toxicogenomics

  15. Understanding microArray data • Typical procedure • Annotate the reporters with something useful (like Entrezgene) • Sort based on fold change and p-value • Search for your favorite genes/proteins • Throw away 95% of the array PET course: Toxicogenomics

  16. Understanding microArray data • “Advanced” procedures • Gene clustering or principal component analysis • Get groups of genes with parallel expression patterns • Useful for diagnosis • Not adding much to understanding (unless combined) PET course: Toxicogenomics

  17. Data analysis overview Slide based on a slide from J. Pennings, RIVM, NL Microarray scans Image analysis Raw data Quality control Normalization Preprocessing Normalized data Statistical analysis List of regulated genes Pattern analysis Gene ontology analysis Promoter analysis Textmining Pathway analysis Untreated (control) Exposed to compound Results

  18. Why Pathway Analysis? • Intuitive to Biologists • Provide a biological context for results • More efficient than searching databases gene-by-gene • Intuitive data display for sharing data • Computation on Pathway Content • Analyze over-representation of changed genes on pathways and ontologies • Network analysis tools PET course: Toxicogenomics

  19. Pathway analysis From lists of differentially expressed genes to biological interpretation. Main Function: Find pathways that are overrepresented in regulated genes Visualize expression changes on pathways PET course: Toxicogenomics

  20. Gene Ontology tools All freely available from internet • Based on Gene Ontology • Onto-Express • GOToolbox  MAPPFinder (GenMAPP) • GO-Elite  GOstat  GeneMerge  GOSurfer   EASE   Fatigo  PET course: Toxicogenomics

  21. GO consortium: www.geneontology.org PET course: Toxicogenomics

  22. Gene Ontology (GO) levels (I) The Gene Ontology (GO) project gives a consistent description of gene products from different databases. PET course: Toxicogenomics

  23. Gene Ontology (GO) levels (II) PET course: Toxicogenomics

  24. Pathway analysis tools • Based on Gene Ontology • Onto-Express • GOToolbox  MAPPFinder (GenMAPP)  GOstat  GeneMerge  GOSurfer   EASE   Fatigo  • Based on pathway maps • (KEGG, BioCarta, custom) • PathVisio • DAVID    • Ingenuity MetaCore (GeneGO)  PET course: Toxicogenomics

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  26. PathVisio www.pathvisio.org • Visualize gene expression on biological pathways • Identify significantly changed processes PET course: Toxicogenomics

  27. Pathway Content • Contributed by research community • Created by GenMAPP group • Contributed by large-scale curation efforts • Converted between species • Distributed on WikiPathways PET course: Toxicogenomics

  28. Identifiers in PathVisio Pathways Experimental Data • Affymetrix, Illumina, Agilent, CodeLink • Entrez Gene • RefSeq (protein only) • Unigene • UniProt • Ensembl • PDB • Entrez Gene • Unigene • UniProt • Ensembl PET course: Toxicogenomics

  29. Gene Database Pathways Experimental Data Gene Database • Genes and annotation • Relational information • Assembled from Ensembl and GO PET course: Toxicogenomics

  30. Supported Species Fruit fly Human Mouse Rat Worm Yeast Zebrafish PET course: Toxicogenomics

  31. Visualize expression results Entrezgene PET course: Toxicogenomics

  32. Example Pathway PET course: Toxicogenomics

  33. Data mapped on Pathway PET course: Toxicogenomics

  34. PathVisio Results: Z-score PET course: Toxicogenomics

  35. Z-score Unchanged gene Changed gene Question: Does the small circle have a higher percentage of changed genes than the large circle? Is this difference significant? PET course: Toxicogenomics

  36. Z-score The Z-score can be used as a measure for how much a subset of genes is different from the rest r = changed genes in Pathway n = total genes in Pathway R = changed genes N = total genes PET course: Toxicogenomics

  37. PathVisio • Advantages: • Easy to use • Reasonable visualization • Some pathway statistics • Interesting content • Mapping of proteomics and metabolomics data • Disadvantages: • Small academic initiative, uncertain lifespan • No change (e.g. time course) visualization • Pathways are not complete (yet) PET course: Toxicogenomics

  38. Sharing Pathways: WikiPathways www.WikiPathways.org • Wiki-technology for editing pathway content • PathVisio applet as pathway editor • Currently ~100 pathways (mouse, rat, human) • Pathway content is accessible to a wider audience • Community “peer review” • Pathway format is exchangeable • Facilitates pathway contribution PET course: Toxicogenomics

  39. http://www.wikipathways.org

  40. Online storage of microarray results PET course: Toxicogenomics

  41. Online storage of microarray results • When publishing papers based on microarray data, one is encouraged (or even obliged) to store the data in online databases • Standards have been developed to describe microarray experiments and data • MIAME: Minimal Information About a Microarray Experiment (http://www.mged.org) • Two main databases exist: • Gene Expression Omnibus (GEO) at NCBI • ArrayExpress at EBI (European Bioinformatics Institute) PET course: Toxicogenomics

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