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6 th InCoB 2007. GS2PATH: Linking Gene Ontology and Pathways. Jin Ok Yang Korean BioInformation Center. KOBIC ( Korean BioInformation Center). The national bioinformatics center of Korea Integration of diverse biological information Genome information Biodiversity information

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gs2path linking gene ontology and pathways

6th InCoB 2007

GS2PATH: Linking Gene Ontology and Pathways

Jin Ok Yang

Korean BioInformation Center

kobic korean bioinformation center
KOBIC (Korean BioInformation Center)
  • The national bioinformatics center of Korea
  • Integration of diverse biological information
      • Genome information
      • Biodiversity information
      • Bioresource information
  • Bioinformatics training
    • International exchange program
  • Collaborative Development of bioinformatic tools
    • Bioportal (Biowiki)
    • Biopipeline (Bioworkflow engine)
biowiki
BioWiki
  • Wiki
    • a web technology that enables anyone to create and update website contents
    • suited for developing online knowledge bases (e.g., Wikipedia )
  • BioWiki
    • To adopt the wiki paradigm in biology
    • Collaborative development of biological knowledge bases
    • BioWiki Contest ( http://biowiki.net )
biopipe http www biopipe net
BioPipe (http://www.biopipe.net)
  • BioWorkFlow Engine
  • No installation required
  • Drag & Drop, and then Connect
  • BioPipe Contest !!
    • Aug 15th ~ Sep 20th
    • Open free Web 2.0

Toolbar

Drag the module from the list and drop it into the design view.

Ontology View

Design View

Monitoring View

gs2path linking gene ontology and pathways5

6th InCoB 2007

GS2PATH: Linking Gene Ontology and Pathways

Jin Ok Yang

Korean BioInformation Center

background
Background

GO &

Pathways

How do you interpret the gene set ?

  • Efforts on analyzing functional relationships among gene sets with GO term and pathways
  • Gene Ontology (GO) Term based analysis  Analysis focused on function
  • GO term related pathways  More useful information
gene set enrichment
Gene set enrichment
  • Enrichment Test
    • Means test to investigate which specific GO term the given gene set has
    • P-value for GO term was calculated by using hyper-geometric probability
  • Gene set enrichment
    • Derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation
    • Evaluates microarray data at the level of gene sets which are defined based on prior biological knowledge
introduction go
Introduction: GO
  • GO databases and tools
  • GO term was used mostly to analyze data sets to identify significant biological changes
  • Pathways also can be exploited to find functional relationships in genes
gs2path
GS2PATH
  • A system to find gene set enrichment in each Gene Ontology (GO) termsand map the part of gene set on GO term into biological pathways (KEGG  and BioCarta)
  • An integrated search tool for analyzing the functional relationships in gene sets and for providing comprehensive results
features
Features
  • Functional relationships between GO term and pathways
  • Hyper-geometric test for gene set enrichment
  • Dual search for up- and down- regulation gene set
  • Various filtering options for GO terms
      • the number of descendant node, evidence of GO terms and statistical values mapping gene set in each GO term
  • User-specified coloring for genes onto pathways
implementation 1 3
Implementation (1/3)
  • GS2Path consists of
    • one internal database (mapping database)
    • four components
        • Query Processor, GO Accessor, KEGG Accessor, and BioCarta Accessor
implementation 2 3
Implementation (2/3)
  • Query Processor
    • receives a user query
    • Converts query into gene related information
    • distributes it to the other components, waiting for receiving results

from them

  • GO Accessor
    • retrieves statistical values mapping gene set in each GO terms to KEGG and BioCarta Pathways
    • Calculates P-value using cumulative hyper-geometric distribution
implementation 3 3
Implementation (3/3)
  • BioCarta and KEGG Accessor
    • retrieve results from BioCarta and KEGG databases, respectively
  • To support user-specified coloring,
    • For KEGG, exploiting the web service API (SOAP/WSDL) of KEGG
    • For BioCarta, no supporting user-defined coloring API. Thus, after retrieving the image of a pathway from BioCarta database, we color genes in the image on-the-fly.
search
Search
  • Gene set enrichment test in organism total profile: GO, KEGG and BioCarta
  • Single or two parts analysis (up and down regulation)
  • Pathway viewer for KEGG and BioCarta
input
Input
  • Database
      • GO category
          • Biological Process
          • Molecular Function
          • Cellular Component
      • Pathways: KEGG and BioCarta
  • Organism
        • Human, Mouse, Rat, and Yeast
  • Gene ID list
slide20
Test
  • Enrichment test
    • P-value: Hyper-geometric probability
    • FDR (False Discovery Rate)
      • Adjustment of p-value
filtering
Filtering
  • GO Term
      • Evidence
      • Slim
      • Number of genes in term
      • P-value
  • Pathways: KEGG and Biocarta
      • Number of genes in term
      • P-value
interface
Interface

Select GO category or Pathways

Select Organism

Put the gene set

conclusion
Conclusion
  • Using Gs2path, users
    • Get the integrated Gene Ontology terms and pathways information together
    • Filter the results with various conditions
    • Capture relationships between Gene Ontology terms and Pathways
  • Available at http://array.kobic.re.kr:8080/arrayport/gs2path/