Difference between revisions of "Module 2: Metabolome-wide genome-wide association study"
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* Slides for introduction to GWAS and metabomatching: [[:File:GWASandMetabomatching.pptx]] | * Slides for introduction to GWAS and metabomatching: [[:File:GWASandMetabomatching.pptx]] | ||
− | * Data | + | * Data: will be distributed by the tutors |
− | * | + | * Code and answers: https://tinyurl.com/y8bymagn |
− | ** | + | |
− | ** | + | * Contents: |
− | ** | + | ** General introduction to the paper/motivation |
− | ** | + | ** Write code to import the data and inspect them |
− | + | ** Run regression analyses between SNP and metabolite features. Plot significance profiles. | |
− | ** | + | ** Matbomatching (sing the PhenoMenal portal: [https://public.phenomenal-h2020.eu] |
+ | ** Wrap-up & evaluation | ||
* Key bioinformatics concept of this module: "Molecular traits as substrate for GWAS. Data in- and export. Regression. Multiple hypotheses testing." | * Key bioinformatics concept of this module: "Molecular traits as substrate for GWAS. Data in- and export. Regression. Multiple hypotheses testing." | ||
* back to [[UNIL MSc course: "Case studies in bioinformatics"]] | * back to [[UNIL MSc course: "Case studies in bioinformatics"]] |
Revision as of 17:15, 1 November 2018
- Title: "Metabolome-wide genome-wide association study or how to link genotypes to metabolites"
- Paper to be examined: “Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links”, PLoS Genet10(2): e1004132. [1]
- Key claim of the paper: "Genetic variants that correlate with any of the measured metabolome features in a large set of individuals generate a signature that facilitates the identification of the metabolite whose concentration is most likely affected by these variants."
- Slides for introduction to GWAS and metabomatching: File:GWASandMetabomatching.pptx
- Data: will be distributed by the tutors
- Code and answers: https://tinyurl.com/y8bymagn
- Contents:
- General introduction to the paper/motivation
- Write code to import the data and inspect them
- Run regression analyses between SNP and metabolite features. Plot significance profiles.
- Matbomatching (sing the PhenoMenal portal: [2]
- Wrap-up & evaluation
- Key bioinformatics concept of this module: "Molecular traits as substrate for GWAS. Data in- and export. Regression. Multiple hypotheses testing."