Exercise 3 - Task 2

Gene regulation networks / Gene ontology

• Use the Cytoscape BiNGO plugin to find statistically overrepresented GO terms of the "Biological Process" category in the network (Top/Bottom 150 from 3.1.2).
  Hint: install the Bingo plugin first
  
  
  • Which are the 15 most prominent/significant (before correction) "Biological Processes"?
    saved table, can be imported into Excel
  • Show (highlight) 5 selected categories in the network (gene expression)
  • Which pathways could be affected by the PGJ2 treatment?


• Restart Cytoscape and import k-means-up-down.txt (up and down regulated clusters) as Table
  
  Up and down regulated clusters: k-means-up-down.txt


• construct a Expression/Correlation network
• Merge expression table with network
• Use the Cytoscape BiNGO plugin to find statistically overrepresented GO terms of the "Molecular Function" category in the network
• Which genes are where annotated with "transcription factor activity"?
• Show their expression profiles as heatmap.

• Map the gene expression data from Wang et al. 2006 to the human apoptosis pathway.
  • Import the human apoptosis signaling pathway from the Pathway Commons database (File -> Import -> Network from public Databases…). Search for human “pathway:apoptosis*”, which was a prominent “Biological Process” in our GO analysis (see the examples for the correct syntax)
    Hint: install the "CyPath2" plugin first
    
    
  • Map the gene expression data to the pathway
    
    Data File: GDS2104-mean.txt
    
    
  • display the Node expression values as colors e.g. 24h (remember 3.1.1).
    
    • File -> Import -> Table -> File...
      Attention: define a mapping from Name to GENE_SYMBOL (Key Column for Networks <-> NAME)
    
    
  • Find nodes/genes that are 2 fold regulated (up/down) in den Apoptosis signaling pathway during PGJ2 treatment. Hint: Use filters
  • Export a list of the genes that are regulated in the Apoptosis signaling pathway
  • Generate their expression profiles in Genesis (as heatmap).


• Map the gene expression data from Wang et al. 2006 to the human p38 MAPK Signaling pathway.
  • Import the human p38 MAPK signaling pathway from the WikiPathways database (File -> Import -> Network from public Databases…). Search for human “p38 MAPK Singaling pathway”, which is affected by PGJ2 (see Wang et al. 2006)
    Hint: install the "WikiPathways" plugin first
    
    
  • Map the gene expression data to the pathway
    
    Data File: GDS2104-mean.txt
    
    
  • display the Node expression values as colors e.g. 24h (remember 3.1.1).
    
    • File -> Import -> Table -> File...
      Attention: define a mapping from "Name" to "shared name"
    
    
  • Make a filter that selects all 2 fold regulated genes from the dataset, which are in the pathway.
  • Export a list of the genes that are regulated in the pathway
  • Generate their expression profiles in Genesis (as heatmap).

• Analyze the Wang et al. 2006 expression data (> 2 fold top/bottom 150 from 3.1.2) using DAVID
  
  http://david.abcc.ncifcrf.gov
  
  
  • Group the regulated genes according to their functional classification
  • How many functional groups did you identify?
  • Identify the transcription factor group and list the transcription factors
  • Find the group for heat shock response:
    
    
    • Report the genes in that group
    • Find all functionally related genes to this group in your gene list (top/bottom 150)
    • Find all highly and very highly functional related genes in the complete human genome
  
  
  • Run Functional Annotation
  • Which KEGG pathways could you identify?
  • Highlight the genes that are involved in the p53-signaling and the MAPK pathway in a graphic representation of the two pathways.