GS2PATH: Linking Gene Ontology and Pathways

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GS2PATH Linking Gene Ontology and Pathways
6th InCoB 2007

• Jin Ok Yang
• Korean BioInformation Center

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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)

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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 )

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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
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GS2PATH Linking Gene Ontology and Pathways
6th InCoB 2007

• Jin Ok Yang
• Korean BioInformation Center

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Background
GO Pathways

• 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

How do you interpret the gene set ?
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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

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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

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Introduction Pathways
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GS2PATH

• A system to find gene set enrichment in each Gene
  Ontology (GO) terms and 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

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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

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Implementation (1/3)

• GS2Path consists of
• one internal database (mapping database)
• four components
• Query Processor, GO Accessor, KEGG Accessor, and
  BioCarta Accessor

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Schema of internal mapping DB
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Architecture
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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

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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.

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GO Term based Pathways Analysis
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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

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Input

• Database
• GO category
• Biological Process
• Molecular Function
• Cellular Component
• Pathways KEGG and BioCarta
• Organism
• Human, Mouse, Rat, and Yeast
• Gene ID list

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Test

• Enrichment test
• P-value Hyper-geometric probability
• FDR (False Discovery Rate)
• Adjustment of p-value

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Filtering

• GO Term
• Evidence
• Slim
• Number of genes in term
• P-value
• Pathways KEGG and Biocarta
• Number of genes in term
• P-value

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Example microarray clustering data
Part A
Part B
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Interface
Select GO category or Pathways
Select Organism
Put the gene set
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Click
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Retaining only GO terms having at least 5 genes
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(No Transcript)
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Select customized colors
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Genes colored in KEGG and BioCarta
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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.kr8080/arraypo
  rt/gs2path/