MIT CompBio Lecture 23 - Multi-Phenotype analyses

MIT Computational Biology: Genomes, Networks, Evolution, Health
Prof. Manolis Kellis
compbio.mit.edu...
Fall 2018
Lecture 23 - Multi-phenotype analyses
1. Motivation of phenome-wide association studies
- PheWAS-informed phenotyping, improved GWAS power, etc
- Electronic health record (EHR) contain rich personalized information
2. Modeling multiple phenotypes in GWAS + epigenomics
- Integration of multiple phenotypes in GWAS from Systems Genetics perspective (clustering approach)
- Direct integration of multiple phenotypes by summary-based factored genetic model estimation
3. Epigenomics of PheWAS
- Risk variants inference using epigenomic reference annotations
- Using disease covariance to improve functional variants inference
- Combining enrichment to improve causal pathway inference
4. Meta-phenotype inference and imputation
- Models leveraging missing information and inferring missing mechanism
- Modeling multimodal electronic health record data
- Imputing missing EHR code and prioritizing patient disease risks
Slides for Lecture 23:
stellar.mit.ed...

[@madihahmanggabarani4638]

This lecture is really helpful for my reserach study, thank you Prof Manolis!