Analytic Tools
- Handling genetic data: Python
- Statistics/graphs: R, SAS, Stata,
- Also have used/familiarity with: SQL, Octave/Mathlab
Analytic Experience:
- causal inference
- survival analysis and cumulative risk
- prospective (longitudinal) and retrospective analyses
- handling missing data and imputation
- GLM and model selection
- Within genetics: PCA, K-means clustering
Topics:
- Mitochondrial DNA and phylogeny
- Head and neck cancer
- Modifiable exposures and cancer
- Modifiable exposures and chronic neurological disease
- Cancer trends
- Disaster aftermath and recovery (e.g. World Trade Center)