Manolis Kellis
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MIT Deep Learning Genomics - Lecture 17 - Genetics2: Systems Genetics
Posted
April 10, 2020
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April 10, 2020
2,579
62
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2.48%
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1:24:09Now PlayingLecture 17 - Genetics 2 - Systems Genetics
MIT 6.874 Lecture 17. Spring 2020
Course website
Lecture 17 slides
Outline: Deep Learning for Human Genetics and Disease
1. Review: GWAS, fine-mapping, Bayesian variant prioritization
2. Deep Learning for GWAS: calling SNPs, prioritize function
3. eQTLs/Mediation: intermediate molecular phenotypes
4. Linear Mixed Models (LMMs) for GWAS and for eQTLcalling
5. Polygenic Risk Scores (PRS): summing over many variants
6. Heritability: definition(s), missing heritability, partitioning
7. LD SCoreregression (LDSC) for fast heritability partitioning
8. Polygenic/Omnigenicdisease models: core vs. periphery
9. Disease gene networks from GWAS evidence boosting
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