High-throughput Biology - From Sequence to Networks 2019 - Lab 14
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Module 14 Practical Lab: Reactome
By Robin Haw
Aim: This exercise will provide you with an opportunity to perform pathway and network analysis using the Reactome Functional Interaction (FI) and the ReactomeFIViz app.
Goal: Analyze gene lists and somatic mutation data to identify biology that contributes to GBM and ovarian cancer.
Example 1: Network-based analysis of GBM gene-sample data
o Open up Cytoscape.
o Go to Apps>Reactome FI and Select “Gene Set/Mutational Analysis”.
o Choose “2017 (Latest)” Version.
o Upload/Browse GBM_genesample.txt file.
o Select “Gene/sample number pair” and Choose sample cutoff value of 4.
o Select “Fetch FI annotations”.
o Click OK.
- Describe the size and composition of the GBM sub-network?
- What are the most frequently mutated genes?
- Describe the TP53-PEG3 interaction, and the source information to support this interaction?
- Describe the data sources for the TAF1-TAF7L FI?
- After clustering, how many modules are there?
- How many pathway gene sets are there in Module 3 when the FDR Filter is set to 0.005 and Module Size Filter to 10?
o Hint: Analyze Module Functions>Pathway Enrichment. Select appropriate filters at each step. - What are the most significant pathway gene sets in Module 0, 2, 3?
o Hint: You don’t need to list them all!
Example 2: Network-based analysis of OvCa somatic mutation
o Open up Cytoscape.
o Go to Apps>Reactome FI and Select “Gene Set/Mutational Analysis”.
o Choose “2017 (Latest)” Version.
o Upload/Browse OVCA_TCGA_MAF.txt file.
o Select “NCI MAF” (Mutation Annotation File) and Choose sample cutoff value of 4.
o Do not select “Fetch FI annotations”.
o Click OK.
- Describe the size and composition of the OvCa network?
- What are the most frequently mutated genes?
- After clustering, how many modules are there?
- How many pathway gene sets are there in Module 1 when the FDR Filter is set to 0.005 and Module Size Filter to 10?
o Hint: Analyze Module Functions>Pathway Enrichment. Select appropriate filters at each step. - What are the most significant pathway gene sets in the first 4 Modules (0 to 4)?
- Do the GO Biological Process annotations correlate with the significant pathway annotations for Module 0?
o Hint: Analyze Module Functions>GO Biological Process. Select appropriate filters at each step. - What are the most significant GO Cell Component gene sets in Module 1 when the FDR Filter is set to 0.005 and Module Size Filter to 10? [Optional]
o Hint: Analyze Module Functions>GO Cell Component. Select appropriate filters at each step. - Are any of the modules annotated with the NCI Disease term: “Stage_IV_Breast_Cancer” [malignant cancer]?
o Hint: Load Cancer Gene Index>Neoplasm>Neoplasm_by_Site>Breast Neoplasm>……. - What are the targets of Docetaxel? o Hint: Overlay Cancer Drugs>Fetch Cancer Drugs. Maybe apply filters?
- How many modules are statistically significant in the CoxPH analysis?
o Hint: Analyze Module Functions>Survival Analysis>Upload/Browse OVCA_TCGA_Clinical.txt. Click OK. - What does the Kaplan-Meyer plot show for the most clinically significant modules?
o 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 (green line), and samples having no genes mutated in the module (red line). - Taking into consideration what you have about module 4, what is your hypothesis?