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Pathways analysis Iowa State Workshop 11 June 2009.

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Presentation on theme: "Pathways analysis Iowa State Workshop 11 June 2009."— Presentation transcript:

1 Pathways analysis Iowa State Workshop 11 June 2009

2 All tools and materials from this workshop are available online at the AgBase database Educational Resources link. For continuing support and assistance please contact: This workshop is supported by USDA CSREES grant number MISV

3 Pathways analysis enables Analysis of data in the context of molecular mechanisms to move beyond statistical analysis of expression to novel biological insights Applying biological filters to focus in on the changes most relevant to experimental model Comparison of affected pathways and phenotypes across platform, time, dose etc (www.ingenuity.com)

4 What regulatory relationships exist between the genes, proteins in my dataset? Which biological and disease processes are most relevant to my genes of interest? Which well-characterized cell signaling and metabolic pathways are most relevant to my experimental data? Networks Functional analysis Metabolic And Signaling pathways

5 Cytoscape Cytoscape is a freely-available (open-source, java-based) bioinformatics software platform for visualizing biological networks (e.g. molecular interaction networks) and analyzing networks with gene expression profiles and other data

6 Core Features Customize network data display using visual styles Powerful graph layout tools Easily organize multiple networks Easily navigate large networks Filter the network Plugin API

7 Cytoscape includes a flexible plugin architecture that enables developers to add extra functionality beyond that provided in the core

8 Some plugins jActiveModules: identify significant “active” subnetworks Expression Correlation Network: cluster expression data Agilent Literature Search: build networks by extracting interactions from scientific literature. MCODE: finds clusters of highly interconnected regions in networks cPath: query, retrieve and visualize interactions from the MSKCC Cancer Pathway database BiNGO: determine which Gene Ontology (GO) categories are statistically over-represented in a set of genes Motif Finder: runs a Gibbs sampling motif detector on sequences for nodes in a Cytoscape network. Exhaustive list at

9 Gene Ontology enrichment analysis BiNGO plugin

10 Gene Ontology structure

11 Analysis tools (commercial) Ingenuity Pathway Analysis Networks Pathways Functions and diseases Gene Ontology (GO) groups Pathway studio GSEA Pathways IPA analysis included as IPA.txt

12 Data curation Ingenuity : Manually curated database by Ph.D level scientists (mining 32 different peer reviewed journals). Pathway studio : Automated curation by Medscan Reader using Natural language processing (NLP) technology. Mining Pubmed abstracts and peer reviewed journals (users can do their own text mining)

13 Comparison Criteria Features Proportion of proteins involved in modeling Data generation Display Test Dataset: 3,600 bovine spermatozoa proteins (Comparison by Divya Swetha Peddinti)

14 FeatureIngenuity Pathway analysis (IPA) Pathway studio InputGI number Microarray ID Affymetrix ID GenBank Swiss Prot Accession Unigene ID Name orAlias HUGO ID Entrez gene GenBank Microarray ID Swiss Prot Accession Unigene ID Name or Alias HUGO ID DatabasesContains biological interactions data for human, mouse, rat Orthologous mapping available for dog, Cow, Chimp, Chicken, Rhesus macaque monkey, Arabidopsis thaliana, Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio Contains biological data for human, mouse, rat, bacteria, chicken, Zebra fish, frog, cow, bee, dog, Arabidopsis, Drosophila, Yeast, and transplantation research etc..

15 Ingenuity Pathway analysis (IPA) Pathway studio Statistical testThe significance value( p value) assigned to the function / pathways using Fischer’s exact test The statistical significance of the overlap between the protein list and a GO group or pathway using the Fischer’s exact test. UpdatesQuarterly NetworksBuilds networks with a maximum of 35 genes/ proteins -

16 Proteins involved in modeling

17 Data generation 37726

18 Pathway display EGF signaling pathway

19 Equally efficient at drawing networks of relationships. IPA : simplifies the pathway display and creates more manageable user friendly network for users to analyze. Pathway Studio: Shows the relations in a table format.

20 Ariadne supported database statistics Mamamlian ResNet 1.5 Million molecular interactions and functional relationships from the entire PubMed (17,000,000 abstracts) and 61 full text journals for 110,435 proteins 13,533 small molecules 2814 cellular processes 2,410 diseases Pathways: 227 Receptor signaling pathways 21 new cellular process regulation pathways Atlas of Signaling - all cellular signaling on one map Plant ResNet Relations to Arabidopsis proteins, (and rice genes that are mapped to Arabidopsis), Protein annotation for eight other plant species; Over 90,000 functional relationships and molecular interactions from 117,000 plant- specific abstracts and 8 plant-specific full-text journals for 71,501 proteins 3,831 small molecules 915 cellular processes 97 plant diseases Pathways: 17 Plant Signaling Pathways 315 AraCyc pathways Journals: Annals of Botany Crop Science Journal of Experimental Botany New Phytologist Plant Cell Plant, Cell and Environment Plant Journal Plant Physiology


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