Pathway and Network Analysis of -Omics Data 2016

Module 4 Lab

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De Novo Subnetwork Clustering Analysis: Reactome

By Robin Haw


This exercise will provide you with an opportunity to perform and network analysis using the Reactome Functional Interaction (FI) and the ReactomeFIViz app.


Analyze somatic mutation data to identify biology that contributes to ovarian cancer.

Example 1: Network-based analysis of OvCa somatic mutation data

  • Open up Cytoscape.

  • Go to Apps>Reactome FI and Select “Gene Set/Mutational Analysis”.

  • Choose “2015 (Latest)” Version.

  • Upload/Browse OVCA_TCGA_MAF.txt file.

  • Select “NCI MAF” (Mutation Annotation File) and Choose sample cutoff value of 4.

  • Do not select “Fetch FI annotations”.

  • Click OK.

  1. Describe the size and composition of the OvCa network?

  2. What are the most frequently mutated genes?

  3. Describe the TP53-PEG3 interaction, and the source information to support this interaction?

  4. Describe the data sources for the RB1-SMARCA4 FI?

  5. After clustering, how many modules are there?

  6. How many pathway gene sets are there in Module 0 when the FDR Filter is set to 0.005 and Module Size Filter to 10?

  • Hint: Analyze Module Functions>Pathway Enrichment. Select appropriate filters at each step.
  1. What are the most significant pathway gene sets in Module 0, 2, 3 and 5?

  2. Do the GO Biological Process annotations correlate with the significant pathway annotations for Module 0?

  • Hint: Analyze Module Functions>GO Biological Process. Select appropriate filters at each step.
  1. What are the most significant GO Cell Component gene sets in Module 3? [Optional]
  • Hint: Analyze Module Functions>GO Cell Component. Select appropriate filters at each step.
  1. Are any of the modules annotated with the NCI Disease term: “Stage_IV_Breast_Cancer” [malignant cancer]?
  • Hint: Load Cancer Gene Index>Neoplasm>Neoplasm_by_Site>Breast Neoplasm>…….
  1. How many modules are statistically significant in the CoxPH analysis?
  1. What does the Kaplan-Meyer plot show for the most clinically significant modules?
  • Hint: Click the most statistically significant module link [blue line] from the CoxPH results panel. Click OK. Click #_plot.pdf to display Kaplan-Meyer plot. Repeat this for the other significant module links. KM plot: samples having genes mutated in a module (red line), and samples having no genes mutated in the module (green line).
  1. Taking into what you have learned about module 2, what is your hypothesis?
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