Difference between revisions of "Module 4: How do "our expectations" confound the results of our analyses?"
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* back to [[UNIL MSc course: "Case studies in bioinformatics 2015"]] | * back to [[UNIL MSc course: "Case studies in bioinformatics 2015"]] | ||
− | * Slides of the lesson of | + | * Slides |
+ | ** Slides of the lesson of Monday Dec. 5th: [[Media:module4_slides_2016.pdf]] | ||
+ | |||
+ | * Data and Code | ||
+ | ** Data and R code for practical exercise [[Media:exercise.zip]] |
Latest revision as of 15:50, 11 December 2016
- Title: "How do "our expectations" confound the results of our analyses?"
- Paper to be examined: “Mutual Exclusivity analysis identifies oncogenic network modules”, Genome Research 2012 22, 398-406 [1]
+ cancer genomic studies from The Cancer Genome Atlas (TCGA).
- Key claim of the paper: "We introduce here a simple but effective method to evaluate the statistical significance of correlations between genomic events, that concurrently preserves both tumor selectivity and tumor heterogeneity"
- Data and Code
- Schedule:
- H1: General introduction to the cancer genomics concepts and motivation introduced in the paper
- H2: The concept of random expectation (the null model)
- H3: How should we model cancer heterogeneity to estimate the significance of mutual exclusivity?
- H4-5: Use R to load and analyze the first cancer genomics dataset (compare alteration distributions and permutation models)
- H6: Reproduce mutual exclusivity analyses proposed in the original paper.
- H7-8: Examine TCGA cancer genomic studies to perform mutual exclusivity analyses under different permutation models
- H9: Summarize and present the results.
- Key bioinformatics concept of this module:
- The importance of the null model (your expectations)
- Properly assessed Mutual Exclusivity inform on biological pathways altered in cancer
- Slides
- Slides of the lesson of Monday Dec. 5th: Media:module4_slides_2016.pdf
- Data and Code
- Data and R code for practical exercise Media:exercise.zip